JP6608314B2 - Image evaluation apparatus, image evaluation method, and image evaluation program - Google Patents

Description

  The present invention relates to an image evaluation apparatus, an image evaluation method, and an image evaluation program, and more particularly to an image evaluation apparatus, an image evaluation method, and an image evaluation program for performing evaluation based on image information.

  2. Description of the Related Art Conventionally, a technique for capturing an image based on user's biological information at the time of capturing an image is known. In Patent Literature 1, when a still image / moving image is shot with a digital still camera / video camera, and when processing on an image, for example, classification / storage / retrieval / reuse, is detected, There is a description that imaging is performed by distinguishing between the case of feeling “cute” and the case of feeling “not interested”.

  In Patent Document 2, when the electroencephalogram information is detected and the electroencephalogram information exceeds the threshold value of the amplitude value recorded as the electroencephalogram condition, the stored electroencephalogram information is erased, and Exif (registered) is displayed on the displayed image. Trademark information is given an index indicating that the user has selected it.

  In Patent Document 3, at least one piece of information of the face size, the position on the face image, the face orientation, the face rotation angle, the face positional relationship when a plurality of faces are included, and the face detection score is included. Based on this, an evaluation value representing the evaluation result of the image is calculated.

Japanese Unexamined Patent Publication No. 2015-127851 JP-A-2015-136377 JP 2008-084047 A

   In Patent Document 1, the quality of an image felt “cute” is not discriminated. For this reason, even if an image is taken with a feeling of “cute”, the quality of the image itself is poor and may not be suitable for photographic prints.

  Further, in Patent Document 2, even if the electroencephalogram information exceeds the threshold value and the image is given the index selected by the user, the quality of the image itself is poor and may not be suitable for photographic prints.

  Further, in Patent Document 3, there is no consideration of the emotional and psychological aspects of the photographer and the subject, so that even if the quality of the image is good, the evaluation value of the image in accordance with the emotion of the user cannot be corrected or presented.

  The present invention provides an image evaluation apparatus, an image evaluation method, and an image evaluation program that can correct an evaluation value of an image based on a criterion according to a psychological state such as emotions of emotion, and can present an appropriate image according to the psychological state to a user. The purpose is to provide.

  In order to solve the above problem, an image evaluation apparatus according to a first aspect of the present invention includes an image information acquisition unit that acquires image information, and a first evaluation value calculation that calculates a first evaluation value based on the image information. A biological information acquisition unit that acquires biological information related to the image information, a correction value calculation unit that calculates a correction value of the first evaluation value based on the biological information, and a first evaluation value based on the correction value And a second evaluation value calculation unit that calculates the second evaluation value of the image information by performing correction.

  According to this invention, the first evaluation value based on the image information is corrected by the correction value based on the biological information, and the second evaluation value of the image information is calculated. As a result, the evaluation value of the image information is corrected based on a criterion corresponding to the psychological state such as emotions of emotions when taking an image, and an appropriate image corresponding to the psychological state can be presented to the user.

  In the image evaluation apparatus according to the second aspect of the present invention, the first evaluation value calculation unit includes the image quality of image information, the resolution, the characters, the shooting date and time, the shooting location, the size of the subject of the image information, the orientation, the angle, A first evaluation value is calculated based on an image information evaluation item including at least one of the positional relationships between subjects.

  Here, at least one of the image information image quality, resolution, characters, shooting date and time, shooting location, subject size, orientation, angle, and positional relationship between the subject is the image data itself, the image data It can be obtained by analysis, incidental information itself of image data, or analysis of incidental information.

  In the image evaluation apparatus according to the third aspect of the present invention, the correction value calculation unit includes at least one of a pulse, a respiratory rate, a body temperature, a sweat amount, and an electroencephalogram of the photographer and / or the subject of the image information, and these A correction value is calculated based on a biological information evaluation item including at least one temporal change amount.

  Here, the biometric information evaluation item including at least one of the pulse, respiration rate, body temperature, sweating amount, and electroencephalogram of the photographer of the image information and / or the subject, and at least one temporal change amount of these is taken. It can be acquired from a wearable terminal or the like that can acquire biological information of a person and / or a subject.

  An image evaluation apparatus according to a fourth aspect of the present invention sets a correction value calculation mode setting unit for setting a mode for calculating a correction value, and sets each weight corresponding to a biological information evaluation item based on the set mode. A biometric information evaluation item weight setting unit that calculates a correction value based on each weight corresponding to the biometric information evaluation item and the biometric information evaluation item.

  As a result, the evaluation item of the image information is corrected after changing the weight indicating the degree of association of the biometric information evaluation item related to emotional and psychological aspects such as emotions and emotions according to the mode, and an appropriate image is displayed to the user. Can be presented.

  In the image evaluation device according to the fifth aspect of the present invention, the biological information evaluation item weight setting unit sets the weight corresponding to the mode set by the correction value calculation mode setting unit to a weight not corresponding to the set mode. Set relatively large.

  Thereby, a more important biological information evaluation item can be reflected in the correction of the first evaluation value, and a more appropriate image can be presented to the user.

  In the image evaluation device according to the sixth aspect of the present invention, the mode is an imaging in which the weight corresponding to the biological information of the photographer of the image information is set to be relatively larger than the weight corresponding to the biological information of the subject of the image information. The subject mode, the subject mode for setting the weight corresponding to the biological information of the subject of the image information relatively larger than the weight corresponding to the biological information of the photographer of the image information, and the biological information of the photographer of the image information This includes any one of the photographer subject modes in which the weight and the weight corresponding to the biological information of the subject of the image information are set equally.

  Accordingly, the biological information of the photographer, the subject, or both can be reflected in the correction of the first evaluation value.

  In the image evaluation apparatus according to the seventh aspect of the present invention, the mode is a biometric information evaluation based on one emotion arbitrarily selected from emotions of the photographer and / or subject of the image information. It includes an emotion selection mode for setting each weight corresponding to the item.

  Thereby, the emotion of the photographer, the subject, or both can be reflected in the correction of the first evaluation value.

  The image evaluation apparatus according to the eighth aspect of the present invention provides image information based on an evaluation reference value setting unit that sets an evaluation reference value serving as a reference for recommending image information, a second evaluation value, and an evaluation reference value. A recommended image classification determination unit that determines whether or not to classify image information into recommended images, and a recommended image classification unit that classifies image information into recommended images according to the determination result.

  Accordingly, the image can be classified as a recommended image based on the second evaluation value reflecting the biological information of the photographer, the subject, or both.

  In the image evaluation device according to the ninth aspect of the present invention, the recommended image classification unit classifies one or a plurality of pieces of image information arbitrarily designated by a user operation into recommended images, and is classified based on the user operation. Or the weight correction part which correct | amends each weight of a biometric information evaluation item based on the biometric information evaluation item corresponding to a some recommended image is provided.

  Thereby, each user's operation can be considered and the weight of each biometric information evaluation item can be corrected.

  In the image evaluation device according to the tenth aspect of the present invention, the recommended image classification unit excludes one or more pieces of image information arbitrarily designated by the user operation from the recommended image, and excludes the recommended image from the recommended image based on the user operation. A weight correction unit is provided for correcting the weight of each biometric information evaluation item based on the biometric information evaluation item corresponding to the one or more image information.

  Thereby, each user's operation can be considered and the weight of each biometric information evaluation item can be corrected.

  In the image evaluation method according to the eleventh aspect of the present invention, a computer acquires image information, calculates a first evaluation value based on the image information, and acquires biological information related to the image information. Calculating a correction value for the first evaluation value based on the biological information; and calculating a second evaluation value for the image information by correcting the first evaluation value based on the correction value. Execute.

  An image evaluation program for causing a computer to execute this image evaluation method is also included in an aspect of the present invention. Note that the image evaluation program can be provided by being recorded in various computer-readable non-transitory computer-readable tangible media.

  According to the present invention, the first evaluation value based on the image information is corrected by the correction value based on the biological information, and the second evaluation value of the image information is calculated. As a result, the evaluation value of the image information is corrected based on a criterion according to the user's psychological state, such as emotions at the time of image capture, and an appropriate image according to the user's psychological state can be presented to the user.

The figure which shows the external appearance of the smart phone 500 and the wearable terminal 1 The figure which shows an example of the correlation of image information and biometric information The block diagram which shows the structure of the smart phone 500 The block diagram which shows the structure of the wearable terminal 1 Recommended image classification process flowchart Flow chart of weight coefficient correction processing

  Hereinafter, embodiments of an image evaluation apparatus, an image evaluation method, and an image evaluation program according to the present invention will be described with reference to the accompanying drawings.

  FIG. 1 is a diagram illustrating the appearance of a smartphone 500 and a wearable terminal 1 to which an image evaluation apparatus, an image evaluation method, and an image evaluation program according to the present invention are applied.

  A smartphone 500 shown in FIG. 1 has a flat housing 502, and a display input in which a display panel 521 as a display unit and an operation panel 522 as an input unit are integrated on one surface of the housing 502. Part 520. The housing 502 includes a speaker 531, a microphone 532, an operation unit 540, a camera unit 541, and a projection unit 542. Note that the configuration of the housing 502 is not limited to this, and for example, a configuration in which the display unit and the input unit are independent, or a configuration having a folding structure and a slide mechanism can be employed.

  As shown in FIG. 1, the wearable terminal 1 is an example of an electronic device that can be worn on a part of a user's body. The wearable terminal 1 can detect biometric information of a user wearing the wearable terminal 1.

  The biological information is information that can be measured from a living body, and typically includes vital signs such as heart rate, pulse, blood pressure, body temperature, respiratory rate, sweating, and electroencephalogram pattern. Alternatively, the number of steps, calorie consumption, etc. may be included.

  Furthermore, the wearable terminal 1 has a display screen 11 (for example, an LCD: Liquid Crystal Display, an organic EL (Electro Luminescence) display, etc.) that is an example of a screen that can display various types of information such as detection results of the user's biological information. A display unit 10, a touch sensor 12 that can detect a touch position that is a position of a touch operation on the display screen 11 of the display unit 10, a fingerprint sensor 13 that is an example of a detection unit that can detect a fingerprint of a user, The operation button 14 is provided on a side surface of the wearable terminal 1 and can input various operations to the wearable terminal 1. That is, in the present embodiment, the display unit 10 and the touch sensor 12 function as a so-called touch panel display. The wearable terminal 1 can communicate with an external device such as the smartphone 500 by wireless communication.

  Although illustration is omitted, it is assumed that there are a plurality of wearable terminals 1 and can be attached to each of a plurality of users such as a photographer and a subject. The smartphone 500 can communicate with each of the plurality of wearable terminals 1 in a distinguishable manner, and can receive the biometric information of each of the plurality of users from each of the wearable terminals 1 in a distinguishable manner.

  The wearable terminal 1 is not limited to the wristwatch type as shown in FIG. 1, and may take various forms such as a glasses type, a ring type, a shoe type, a pocket type, and a pendant type.

  The smartphone 500 can store the biological information received from the wearable terminal 1 in association with the image data. For example, as illustrated in FIG. 2, the smartphone 500 stores image data and its shooting date and time in association with each other using image data supplementary information such as an Exif (registered trademark) file tag. At the same time, the smartphone 500 uses the identification time as the image data capture time point to capture the biometric information of the photographer and subject detected at or near the image data capture time file (CSV file, etc.) separate from the Exif file. May be stored as The storage area of the Exif file and the biometric information file may be separate or the same.

  Alternatively, the image of the smartphone 500 is stored with the image data and the shooting date / time associated with each other by using supplementary information such as a tag of the Exif file. On the other hand, the wearable terminal 1 immediately acquires information about the shooting date and time of the image data from the smartphone 500 at the time of shooting, and uses this as an identification key to detect the living body of the photographer and subject detected at or near the shooting time of the image data. Information may be stored. Instead of using the shooting time as an identification key, an Exif file storage time, an image preview time, or the like can be used as an identification key. If the wearable terminal 1 can acquire the position information, a set of the shooting time point and the position information may be used as the identification key.

  Or the smart phone 500 may memorize | store the photographer and the biometric information of a to-be-photographed object received from the wearable terminal 1 in the Exif file etc. as incidental information of image data received from the wearable terminal 1 at the time of image | photographing image data. In this specification, image data and incidental information are collectively referred to as image information. The biometric information related to the image information is associated with the image data by using a specific time point such as the biometric information and the shooting time point included in the incidental information associated with the image data in the image file as a key. Both biometric information. In addition, the storage location of the biological information related to the image information may be the same as or different from the image data.

  FIG. 3 is a block diagram showing the configuration of the smartphone 500 shown in FIG. As shown in FIG. 3, as a main component of the smartphone 500, a wireless communication unit 510, a display input unit 520, a call unit 530, an operation unit 540, a camera unit 541 functioning as an imaging unit, and a storage unit 550 An external input / output unit 560, a GPS (Global Positioning System) receiving unit 570, a motion sensor unit 580, a power supply unit 590, and a main control unit 501. In addition, as a main function of the smartphone 500, a wireless communication unit 510 that performs mobile wireless communication via a base station device and a mobile communication network is provided.

  The wireless communication unit 510 performs wireless communication with a base station apparatus accommodated in the mobile communication network in accordance with an instruction from the main control unit 501. Using this wireless communication, transmission and reception of various file data such as audio data and image data, e-mail data, and reception of Web data and streaming data are performed.

  The display input unit 520 displays images (still images and moving images), character information, and the like visually by the control of the main control unit 501, and visually transmits information to the user, and detects user operations on the displayed information. This is a so-called touch panel, and includes a display panel 521 and an operation panel 522. When viewing the generated three-dimensional image, the display panel 521 is preferably a three-dimensional display panel.

  The display panel 521 uses an LCD (Liquid Crystal Display), an OELD (Organic Electro-Luminescence Display), or the like as a display device.

  The operation panel 522 is a device that is placed so that an image displayed on the display surface of the display panel 521 is visible and detects one or a plurality of coordinates operated by a user's finger or stylus. When this device is operated by a user's finger or stylus, a detection signal generated due to the operation is output to the main control unit 501. Next, the main control unit 501 detects an operation position (coordinates) on the display panel 521 based on the received detection signal.

  As shown in FIG. 1, the display panel 521 and the operation panel 522 of the smartphone 500 integrally form the display input unit 520, but the operation panel 522 is disposed so as to completely cover the display panel 521. ing. When this arrangement is adopted, the operation panel 522 may have a function of detecting a user operation even in an area outside the display panel 521. In other words, the operation panel 522 includes a detection area (hereinafter referred to as a display area) for an overlapping portion that overlaps the display panel 521 and a detection area (hereinafter, a non-display area) for an outer edge portion that does not overlap the other display panel 521. May be included).

  Note that the size of the display area and the size of the display panel 521 may be completely matched, but it is not always necessary to match the two. In addition, the operation panel 522 may include two sensitive regions of the outer edge portion and the other inner portion. Further, the width of the outer edge portion is appropriately designed according to the size of the housing 502 and the like. Furthermore, examples of the position detection method employed in the operation panel 522 include a matrix switch method, a resistance film method, a surface acoustic wave method, an infrared method, an electromagnetic induction method, and a capacitance method. You can also

  The call unit 530 includes a speaker 531 and a microphone 532, and converts a user's voice input through the microphone 532 into voice data that can be processed by the main control unit 501, and outputs the voice data to the main control unit 501, or a wireless communication unit 510 or the audio data received by the external input / output unit 560 is decoded and output from the speaker 531. As shown in FIG. 1, for example, the speaker 531 and the microphone 532 can be mounted on the same surface as the surface on which the display input unit 520 is provided.

  The operation unit 540 is a hardware key using a key switch or the like, and receives an instruction from the user. For example, the operation unit 540 is mounted on a lower portion and a lower side of the display unit of the housing 502 of the smartphone 500 and is turned on when pressed with a finger or the like, and is turned off when a finger is released with a restoring force such as a spring. It is a button type switch.

  The storage unit 550 includes control programs and control data of the main control unit 501, address data in which names and telephone numbers of communication partners are associated, transmitted and received e-mail data, Web data downloaded by Web browsing, and downloaded contents Data is stored, and streaming data and the like are temporarily stored. The storage unit 550 includes an internal storage unit 551 with a built-in smartphone and an external storage unit 552 having a removable external memory slot. Each of the internal storage unit 551 and the external storage unit 552 constituting the storage unit 550 includes a flash memory type, a hard disk type, a multimedia card micro type, a multimedia card micro type, It is realized using a storage medium such as a card type memory (for example, Micro SD (registered trademark) memory), a RAM (Random Access Memory), a ROM (Read Only Memory), or the like.

  The external input / output unit 560 serves as an interface with all external devices connected to the smartphone 500, and communicates with other external devices (for example, a universal serial bus) or a network (for example, the Internet, Wireless LAN (Local Area Network), Bluetooth (registered trademark), RFID (Radio Frequency Identification), infrared communication (Infrared Data Association: IrDA), UWB (Ultra Wideband) (registered trademark), ZigBee (registered) Trademark) etc.) for direct or indirect connection.

  External devices connected to the smartphone 500 include, for example, a wired / wireless headset, wired / wireless external charger, wired / wireless data port, a memory card connected via a card socket, and a SIM (Subscriber). Identity Module Card) / UIM (User Identity Module Card) card, external audio / video equipment connected via audio / video I / O (Input / Output) terminal, external audio / video equipment connected wirelessly, yes / no There are wirelessly connected smart phones, wired / wireless connected personal computers, wired / wireless connected PDAs, earphones, and the like. The external input / output unit 560 transmits data received from such an external device to each component inside the smartphone 500, or allows the data inside the smartphone 500 to be transmitted to the external device. Can do.

  The GPS receiving unit 570 receives GPS signals transmitted from the GPS satellites ST1 to STn in accordance with instructions from the main control unit 501, performs positioning calculation processing based on the received plurality of GPS signals, and calculates the latitude and longitude of the smartphone 500. , Detect the position consisting of altitude. When the GPS receiving unit 570 can acquire position information from the wireless communication unit 510 or the external input / output unit 560 (for example, a wireless LAN), the GPS receiving unit 570 can also detect the position using the position information.

  The motion sensor unit 580 includes, for example, a three-axis acceleration sensor, and detects the physical movement of the smartphone 500 in accordance with an instruction from the main control unit 501. By detecting the physical movement of the smartphone 500, the moving direction and acceleration of the smartphone 500 are detected. This detection result is output to the main control unit 501.

  The power supply unit 590 supplies power stored in a battery (not shown) to each unit of the smartphone 500 in accordance with an instruction from the main control unit 501.

  The main control unit 501 includes a microprocessor, operates according to a control program and control data stored in the storage unit 550, and controls each unit of the smartphone 500 in an integrated manner. Further, the main control unit 501 includes a mobile communication control function for controlling each unit of the communication system and an application processing function in order to perform voice communication and data communication through the wireless communication unit 510.

  The application processing function is realized by the main control unit 501 operating in accordance with application software stored in the storage unit 550. Application processing functions include, for example, an infrared communication function that controls the external input / output unit 560 to perform data communication with the opposite device, an e-mail function that transmits and receives e-mails, and a web browsing function that browses web pages. .

  The main control unit 501 also has an image processing function such as displaying video on the display input unit 520 based on image data (still image or moving image data) such as received data or downloaded streaming data. The image processing function is a function in which the main control unit 501 decodes the image data, performs image processing on the decoding result, and displays an image on the display input unit 520.

  Further, the main control unit 501 executes display control for the display panel 521 and operation detection control for detecting a user operation through the operation unit 540 and the operation panel 522.

  By executing the display control, the main control unit 501 displays an icon for starting application software, a software key such as a scroll bar, or a window for creating an e-mail. Note that the scroll bar refers to a software key for accepting an instruction to move the display portion of a large image that does not fit in the display area of the display panel 521.

  Further, by executing the operation detection control, the main control unit 501 detects a user operation through the operation unit 540, or accepts an operation on the icon or an input of a character string in the input field of the window through the operation panel 522. Or a display image scroll request through a scroll bar.

  Furthermore, by executing the operation detection control, the main control unit 501 causes the operation position with respect to the operation panel 522 to overlap with the display panel 521 (display area) or other outer edge part (non-display area) that does not overlap with the display panel 521. And a touch panel control function for controlling the sensitive area of the operation panel 522 and the display position of the software key.

  The main control unit 501 can also detect a gesture operation on the operation panel 522 and execute a preset function in accordance with the detected gesture operation. Gesture operation is not a conventional simple touch operation, but an operation that draws a trajectory with a finger or the like, designates a plurality of positions at the same time, or combines these to draw a trajectory for at least one of a plurality of positions. means.

  The camera unit 541 (corresponding to an image information acquisition unit) is an imaging device that performs electronic imaging using an image sensor such as a CMOS (Complementary Metal Oxide Semiconductor) or a CCD (Charge-Coupled Device).

  In addition, the camera unit 541 converts image data of visible light obtained by imaging into compressed image data such as JPEG (Joint Photographic coding Experts Group) under the control of the main control unit 501, and records it in the storage unit 550. Can be output through the external input / output unit 560 or the wireless communication unit 510, and similarly, a distance image indicating the distance of the subject can be recorded in the storage unit 550 or output through the external input / output unit 560 or the wireless communication unit 510. can do. In the smartphone 500 shown in FIG. 3, the camera unit 541 is mounted on the same surface as the display input unit 520, but the mounting position of the camera unit 541 is not limited to this and may be mounted on the back surface of the display input unit 520. Alternatively, a plurality of camera units 541 may be mounted. Note that when a plurality of camera units 541 are mounted, the camera unit 541 used for imaging can be switched to perform imaging alone, or the plurality of camera units 541 can be used for imaging simultaneously.

  The camera unit 541 can be used for various functions of the smartphone 500. For example, an image acquired by the camera unit 541 can be displayed on the display panel 521, or the image of the camera unit 541 can be used as one of operation inputs of the operation panel 522. Further, when the GPS receiving unit 570 detects the position, the position can also be detected with reference to an image from the camera unit 541. Further, referring to the image from the camera unit 541, the optical axis direction of the camera unit 541 of the smartphone 500 is determined without using the triaxial acceleration sensor or in combination with the triaxial acceleration sensor. It is also possible to determine the current usage environment. Of course, the image from the camera unit 541 can be used in the application software.

  FIG. 4 is a block diagram illustrating a hardware configuration of the wearable terminal 1. As illustrated in FIG. 4, the wearable terminal 1 includes a display unit 10, a touch sensor 12, a fingerprint sensor 13, an operation button 14, a controller 101, a storage unit 102, a biological information sensor 103, and a communication unit 104.

  The controller 101 is configured by a CPU (Central Processing Unit) and the like, and controls each unit included in the wearable terminal 1 by executing a program stored in the storage unit 102. The storage unit 102 includes a ROM (Read Only Memory), a RAM (Random Access Memory), and the like, and can store various information such as a program executed by the controller 101 and data used when the controller 101 executes the program. is there. The biological information sensor 103 can detect biological information (for example, body temperature, amount of sweat, pulse, brain wave) of the user wearing the wearable terminal 1. The communication unit 104 can communicate with an external device such as the smartphone 500 by wireless communication. Note that the user of the wearable terminal 1, that is, the photographer or subject of the image data is mainly a person, but the animal that is the subject may be the user of the wearable terminal 1 as long as the biological information of the animal can be detected. For example, a collar-type wearable terminal 1 that detects the body temperature of a dog or cat can be used.

  When the wearable terminal 1 is not a wristwatch type, for example, a glasses type, the wearer's gaze direction, facial expression, retinal shape, iris shape, fingerprint, voiceprint, ear shape, blink, walking vibration, etc. can be acquired as biological information. May be.

  FIG. 5 shows a flowchart of recommended image classification processing executed by the smartphone 500. It is assumed that a program for causing the main control unit 501 of the smartphone 500 to execute each step of the recommended image classification process is stored in a computer-readable non-transitory tangible medium such as the internal storage unit 551.

  In S1 (first evaluation value calculation step), the main control unit 501 stores the evaluation value of the image data from the evaluation item of the image data for one piece of image data stored in the storage unit 550 and arbitrarily selected. A certain first evaluation value is calculated. The one or more pieces of image information stored in the storage unit 550 are image information captured by the camera unit 541 of the smartphone 500, a digital camera other than the camera unit 541, and the like. The main control unit 501 that executes the first evaluation value calculation step corresponds to a first evaluation value calculation unit.

  The method for calculating the evaluation items of the image data can be performed in the same manner as in Patent Document 3. In the following, as an example, the evaluation items of the image data are the face size, the position on the face image, the face orientation, the face rotation angle, the positional relationship between faces when a plurality of faces are included, and the face detection. Assume that it is a score. The evaluation items for these image data are directly obtained from the image data itself, the Exif file tag or other additional information for storing the image data, or the additional information stored in a storage area separate from the image data. Or they can be obtained by analyzing them.

The individual evaluation values A _{1 to} A ₆ for each evaluation item of the image data are the face size, the position on the face image, the face orientation, the face rotation angle, and the faces when there are multiple faces. It is assumed that the positional relationship and the face detection score are numerical values. The individual evaluation values A _{1 to} A ₆ for each of these evaluation items may be calculated from the image data itself or from the incidental information of the image data.

The first evaluation value is calculated based on the individual evaluation values A _{1 to} A ₆ for each of these evaluation items. As an example, the first evaluation value Ef0 is calculated by the following equation.

Ef0 = α ₁ A ₁ + α ₂ A ₂ + α ₃ A ₃ + α ₄ A ₄ + α ₅ A ₅ + α ₆ A ₆
Here, α _{1 to} α ₆ are weights corresponding to the evaluation values A _{1 to} A ₆ for each evaluation item of the image information. These weights α _{1 to} α ₆ may be arbitrarily set by the user, or may be changed according to the contents of the image data and the accompanying information. Furthermore, the weights α _{1 to} α ₆ may vary according to a shooting mode and an emotion mode described later.

  Further, the evaluation items serving as the calculation criteria for the first evaluation value Ef0 are not limited to the above. For example, the evaluation items may include image data quality, resolution, characters, shooting date and time, shooting location, and the like. These evaluation items can be acquired by image analysis, person recognition, analysis of incidental information, and the like. Furthermore, weights corresponding to individual evaluation values for each of these evaluation items may be set as appropriate.

  In S <b> 2 (shooting mode determination step), the main control unit 501 sets an arbitrary shooting mode from among “shooter mode”, “subject mode”, and “shooter / subject mode” via the operation unit 540. Accept. The main control unit 501 determines whether the photographing mode received via the operation unit 540 is “photographer mode”, “subject mode”, or “photographer / subject mode”. If the photographing mode is “photographer mode”, the process proceeds to S3, if “photographer mode”, the process proceeds to S4, and if “photographer / subject mode”, the process proceeds to S5. The main control unit 501 that executes this shooting mode determination step corresponds to a correction value calculation mode setting unit.

  In S3 (photographer mode weight setting step), the main control unit 501 sets the weight of the correction value corresponding to the “photographer mode”. For example, the correction value weight X = 1 based on the photographer's biometric information and the correction value weight Y = 0 based on the subject's biometric information are set. The main control unit 501 that executes this photographer mode weight setting step corresponds to a biometric information evaluation item weight setting unit.

  In S4 (subject mode weight setting step), the main control unit 501 sets the weight of the correction value of the image evaluation value corresponding to the “subject mode”. For example, the correction value weight X = 0 based on the photographer's biometric information and the correction value weight Y = 1 based on the biometric information of the subject are set. The main control unit 501 that executes this subject mode weight setting step corresponds to a biological information evaluation item weight setting unit.

  In S5 (photographer / subject mode weight setting step), the main control unit 501 sets the weight of the correction value of the image evaluation value corresponding to the “photographer / subject mode”. For example, the correction value weight X based on the photographer's biological information X = 0.5 and the correction value weight Y based on the biological information of the subject are set to 0.5. The main control unit 501 that executes this photographer / subject mode weight setting step corresponds to a biometric information evaluation item weight setting unit.

  In S6 (emotion mode determination step), the main control unit 501 uses the operation unit 540 to select one of the four emotion modes of “joy mode”, “anger mode”, “sad mode”, and “easy mode”. Accept any emotion mode settings. The main control unit 501 determines whether the emotion mode received via the operation unit 540 is “joy mode”, “anger mode”, “sad mode”, or “easy mode”. When the emotion mode is “joy mode”, the process proceeds to S7, when “anger mode” is selected, the process proceeds to S8, when “sad mode” is selected, the process proceeds to S9.

In S7 (joy mode weight setting step), the main control unit 501 sets the weight of the image evaluation value corresponding to “joy mode”. For example, if Z ₁ is a weight factor of “joy”, Z ₂ is a weight factor of “anger”, Z ₃ is a weight factor of “sorrow”, and Z ₄ is a weight factor of “easy”,
Z ₁ = 1, Z ₂ = Z ₃ = Z ₄ = 0
And set.

In S8 (anger mode weight setting step), the main control unit 501 sets the weight of the image evaluation value corresponding to the “anger mode”. For example,
Z ₂ = 1, Z ₁ = Z ₃ = Z ₄ = 0
And set.

In S9 (sad mode weight setting step), the main control unit 501 sets the weight of the image evaluation value corresponding to the “sad mode”. For example,
Z ₃ = 1, Z ₁ = Z ₂ = Z ₄ = 0
And set.

In S10 (easy mode weight setting step), the main control unit 501 sets the weight of the image evaluation value corresponding to the “easy mode”. For example,
Z ₄ = 1, Z ₁ = Z ₂ = Z ₃ = 0
And set.

Note that the values of Z ₁ , Z ₂ , Z ₃ , and Z ₄ according to the emotion mode setting are not limited to the above. For example, in the case of “joy mode”, Z ₁ = 0.7, Z ₂ = Z ₃ = Z ₄ = 0.1 may be used.

  In S11 (biometric information acquisition and second evaluation value calculation step), the main control unit 501 acquires the biological information of the photographer and the subject related to the image data. Then, the main control unit 501 calculates a second evaluation value Ef obtained by correcting the first evaluation value Ef0 with a correction value calculated from the biological information to which the weights S3 to 5 and S7 to 10 are given. Specifically, the second evaluation value Ef is calculated by the following mathematical formula. The main control unit 501 that executes this biometric information acquisition and second evaluation value calculation step corresponds to a correction value calculation unit.

Ef = Ef0 + (Ef1 + Ef2 + Ef3 + Ef4) * X + (Ef5 + Ef6 + Ef7 + Ef8) * Y
However, Ef1, Ef2, Ef3, and Ef4 are correction values based on the photographer's biological information, and Ef5, Ef6, Ef7, and Ef8 are correction values based on the average of the biological information of the subject n, and are calculated by the following equations.

Ef1 = (β ₁ Cp + β ₂ Dp + β ₃ Ep + β ₄ Fp + β ₅ Gp + β ₆ Hp) × Z ₁
Ef2 = (γ ₁ Cp + γ ₂ Dp + γ ₃ Ep + γ ₄ Fp + γ ₅ Gp + γ ₆ Hp) × Z ₂
Ef3 = (ω ₁ Cp + ω ₂ Dp + ω ₃ Ep + ω ₄ Fp + ω ₅ Gp + ω ₆ Hp) × Z ₃
Ef4 = (λ ₁ Cp + λ ₂ Dp + λ ₃ Ep + λ ₄ Fp + λ ₅ Gp + λ ₆ Hp) × Z ₄
Ef5 = {(β ₁ C1 + β ₂ D1 + β ₃ E1 + β ₄ F1 + β ₅ G1 + β ₆ H1) + ... + (β ₁ Cn + β ₂ Dn + β ₃ En + β ₄ Fn + β ₅ Gn + β ₆ Hn)} / n × Z ₁
Ef6 = {(γ ₁ C1 + γ ₂ D1 + γ ₃ E1 + γ ₄ F1 + γ ₅ G1 + γ ₆ H1) + ... + (γ ₁ Cn + γ ₂ Dn + γ ₃ En + γ ₄ Fn + γ ₅ Gn + γ ₆ Hn)} / n × Z ₂
Ef7 = {(ω ₁ C1 + ω ₂ D1 + ω ₃ E1 + ω ₄ F1 + ω ₅ G1 + ω ₆ H1) + ... + (ω ₁ Cn + ω ₂ Dn + ω ₃ En + ω ₄ Fn + _{ω 5 Gn + ω 6 Hn)} } / n × Z 3
Ef8 = {(λ ₁ C1 + λ ₂ D1 + λ ₃ E1 + λ ₄ F1 + λ ₅ G1 + λ ₆ H1) + ... + (λ ₁ Cn + λ ₂ Dn + λ ₃ En + λ ₄ Fn + λ ₅ Gn + λ ₆ Hn)} / n × Z ₄
Here, Cp, Dp, Ep, Fp, Gp, and Hp are the pulse rate, respiratory rate, blood pressure, sweating, electroencephalogram, and their changes in the photographer of the image data, respectively. These are acquired from the wearable terminal 1 worn by the photographer at the time of photographing the image data (at the time of photographing or in the vicinity thereof).

  Cn, Dn, En, Fn, Gn, and Hn (n = 1, 2, ....) are the pulse rate, respiratory rate, and blood pressure of subject n (n = 1, 2, ....), respectively. Sweating, brain waves, and their changes. These are acquired from the wearable terminal 1 attached to each of the subjects n at the time of image data shooting (at the date of shooting or in the vicinity thereof).

Β _{1 to} β ₆ are weighting factors of biological information of pulse rate, respiratory rate, blood pressure, sweating, electroencephalogram, and their changes related to the feeling of “joy” of the photographer or subject, γ _{1 to} γ ₆ is a weighting coefficient of each biometric information related to the emotion of "anger" of the photographer or the subject, ω ₁ ~ω ₆ is a weighting coefficient of each biometric information related to the emotion of the "sorrow" of the photographer or the subject, λ ₁ ˜λ ₆ is a weighting coefficient of each piece of biometric information related to the “easy” feeling of the photographer or subject. As these weighting factors, a value of 0 or more and 1 or less is set in advance in accordance with the strength of relevance of each biological information to each emotion of the photographer or the subject.

For example, the pulse weighting factor β ₁ = 0.8 related to the emotion of “joy”, the pulse weighting factor γ ₁ = 1 related to the emotion of “anger”, the weight of the pulse rate related to the emotion of “sorrow” The coefficient ω ₁ = 0.1, the pulse weight weight coefficient λ ₁ = 0.5 related to the emotion of “Easy”, and the like. These weights are experienced by the degree of reflection in each biological information for each emotion that the pulse rate increases significantly when the emotion of “anger” increases, but the pulse rate does not change greatly even if the emotion of “sorrow” increases. Is determined. The main control unit 501 that executes the biometric information acquisition and the second evaluation value calculation step corresponds to a biometric information acquisition unit and a second evaluation value calculation unit.

  In S12 (reference value setting and recommended image determination step), the main control unit 501 sets a recommended image reference value Eth. The reference value Eth is set based on a user operation via the operation unit 540, a value stored in the storage unit 550 in advance, or the like. The main control unit 501 determines whether or not the second evaluation value Ef has reached the reference value Eth for the recommended image. If it is determined that Ef ≧ Eth, the process proceeds to S13. If it is determined that Ef <Eth, the process ends. The main control unit 501 that executes the reference value setting and recommended image determination step corresponds to an evaluation reference value setting unit and a recommended image classification determination unit.

  In S13 (recommended image classification step), the image data is classified into recommended images. The classification is performed by adding a flag indicating a recommended image to the image data or moving the image data to a specific folder for recommended images. The main control unit 501 that executes this recommended image classification step corresponds to a recommended image classification unit.

  In the recommended image classification process, S11 to S13 may be repeatedly executed for each of a plurality of arbitrary image data stored in the storage unit 550. As a result, arbitrary image data stored in the storage unit 550 is classified into a recommended image and a non-recommended image (non-recommended image) under a specific shooting / subject mode and emotion mode that are arbitrarily set. Is done.

  FIG. 6 is a flowchart of the weighting factor correction process executed by the smartphone 500. It is assumed that a program for causing the main control unit 501 of the smartphone 500 to execute each step of the weight coefficient correction processing is stored in a computer-readable non-transitory tangible medium such as the internal storage unit 551. This process is performed after the classification of the recommended image is completed by executing the recommended image classification process.

  In S21 (recommended image deletion determination step), the main control unit 501 categorizes images as recommended images under the specific shooting mode and emotion mode set in the recommended image classification process via the operation unit 540. It is determined whether or not an operation has been performed to delete one or more image data arbitrarily selected from the data from the recommended image classification. If Yes, the process proceeds to S22, and if No, the process proceeds to S23.

  In S22 (recommended image deletion step), the main control unit 501 deletes the image data on which the deletion operation has been performed from the recommended image classification, and adds biometric information related to the image data to the deleted image biometric information list. .

  In S23 (recommended image addition determination step), the main control unit 501 uses the operation unit 540 to select one or a plurality of images arbitrarily selected from image data not classified as recommended images as recommended images. It is determined whether or not an operation to be added to the classification has been performed. If Yes, the process proceeds to S24, and if No, the process proceeds to S25.

  In S24 (recommended image adding step), the main control unit 501 classifies the image data on which the additional operation has been performed as a recommended image, and adds biometric information related to the image data to the additional image biometric information list.

S25, (weight correction step), the main control unit 501, the biological information of the deletion image biometric information list, from the biometric information of the additional image biometric information list, the weighting coefficient β ₁ ~β ₆ of the biological information, gamma ₁ to? ₆ , ω _{1 to} ω ₆ and λ _{1 to} λ ₆ are corrected. The main control unit 501 that executes this weight correction step corresponds to a weight correction unit. When there is no biometric information in the deleted image biometric information list, biometric information weighting factors β _{1 to} β ₆ , γ _{1 to} γ ₆ , ω _{1 to} ω ₆ , λ _{1 are} obtained from the biometric information in the additional image biometric information list. ˜λ ₆ shall be corrected. If there is no biometric information in the additional image biometric information list, the biometric information weight coefficients β _{1 to} β ₆ , γ _{1 to} γ ₆ , ω _{1 to} ω ₆ , λ _{1 to} λ are obtained from the biometric information in the deleted image biometric information list. ₆ shall be corrected.

Specifically, for example, the photographer's pulse rate, respiratory rate, blood pressure, sweating amount, brain wave related to all image data for which the second evaluation value Ef has been calculated under “photographer mode” and “joy mode” And the average value of the changes. Let these be Avg (B ₁ ), Avg (B ₂ ), Avg (B ₃ ), Avg (B ₄ ), Avg (B ₅ ), Avg (B ₆ ).

Next, an average value of the photographer's pulse rate, respiratory rate, blood pressure, sweating amount, brain wave and change amount related to the images in the additional image biometric information list is obtained. Let these be Avg (Ba ₁ ), Avg (Ba ₂ ), Avg (Ba ₃ ), Avg (Ba ₄ ), Avg (Ba ₅ ), Avg (Ba ₆ ).

Next, an average value of the photographer's pulse rate, respiratory rate, blood pressure, sweating amount, brain wave, and change amount related to the image of the deleted image biometric information list is obtained. Let these be Avg (Bd ₁ ), Avg (Bd ₂ ), Avg (Bd ₃ ), Avg (Bd ₄ ), Avg (Bd ₅ ), Avg (Bd ₆ ).

Next, these differences Δ _{1 to} Δ ₆ are obtained. That is, Δ ₁ = (Avg (B ₁ )-Avg (Ba ₁ )) + (Avg (Bd ₁ )-Avg (B ₁ ))
Δ ₂ = (Avg (B ₂ )-Avg (Ba ₂ )) + (Avg (Bd ₂ )-Avg (B ₂ ))
Δ ₃ = (Avg (B ₃ )-Avg (Ba ₃ )) + (Avg (Bd ₃ )-Avg (B ₃ ))
Δ ₄ = (Avg (B ₄ )-Avg (Ba ₄ )) + (Avg (Bd ₄ )-Avg (B ₄ ))
Δ ₅ = (Avg (B ₅ )-Avg (Ba ₅ )) + (Avg (Bd ₅ )-Avg (B ₅ ))
Δ ₆ = (Avg (B ₆ )-Avg (Ba ₆ )) + (Avg (Bd ₆ )-Avg (B ₆ ))
Next, the parameter M having the largest value among Δ _{1 to} Δ ₆ and the subscript m of the M are specified. Ie
[M, m] = max (Δ ₁ , Δ ₂ , Δ ₃ , Δ ₄ , Δ ₅ , Δ ₆ )
It is.

Then, the weighting coefficient β _m related to the emotion of “joy” is corrected by the following expression, and this is set as a new weighting coefficient β _m .

{(Avg (B _m ) -Avg (Ba _m )) + (Avg (Bd _m ) -Avg (B _m ))} / Avg (B _m ) * β _m + β _m → β _m
This is a correction for increasing the weight of the biometric information related to the recommended image additionally selected by the user in S24 and reducing the weight of the biometric information related to the recommended image deleted by the user in S22.

Depending on the shooting / subject mode, using the biometric information of the photographer and / or the subject n, the same correction is applied to the weighting factors γ _{1 to} γ ₆ related to the emotions of “anger”, “sadness”, “easy”, This can also be performed for ω _{1 to} ω ₆ and λ _{1 to} λ ₆ . That is,
Under “Photographer mode” and “Anger mode”
{(Avg (B _m ) -Avg (Ba _m )) + (Avg (Bd _m ) -Avg (B _m ))} / Avg (B _m ) * γ _m + γ _m → γ _m
Under “Photographer mode” and “Sad mode”
{(Avg (B _m ) -Avg (Ba _m )) + (Avg (Bd _m ) -Avg (B _m ))} / Avg (B _m ) * ω _m + ω _m → ω _m
Under “Photographer mode” and “Easy mode”
{(Avg (B _m ) -Avg (Ba _m )) + (Avg (Bd _m ) -Avg (B _m ))} / Avg (B _m ) * λ _m + λ _m → λ _m
In addition, under the “subject mode” and the “joy mode”, the above differences Δ _{1 to} Δ ₆ are calculated using the average value of the biometric information of each subject n in the additional image biometric information list, instead of the biometric information of the photographer, and The average value of the biological information of each subject n in the deleted image biological information list is obtained, and β ₁ to β ₆ , γ _{1 to} γ ₆ , ω _{1 to} ω ₆ , and λ _{1 to} λ ₆ are corrected according to this value.

That is, the average of the pulse rate, respiratory rate, blood pressure, sweating amount, electroencephalogram and the amount of change of each subject related to each image data for which the second evaluation value Ef has been calculated under “subject mode” and “joy mode” Find the value. These are designated as Avg (BS ₁ ), Avg (BS ₂ ), Avg (BS ₃ ), Avg (BS ₄ ), Avg (BS ₅ ), Avg (BS ₆ ).

In addition, the average value of the pulse rate, respiratory rate, blood pressure, sweating amount, brain wave and change amount of each subject (one or more) in the additional image biometric information list is expressed as Avg (BSa ₁ ), Avg (BSa ₂ ), Avg (BSa ₃ ), Avg (BSa ₄ ), Avg (BSa ₅ ), Avg (BSa ₆ ), and the pulse rate, respiratory rate, blood pressure, sweat rate, brain wave of each subject (one or more) in the deleted image biometric information list The average values of the changes are Avg (BSd ₁ ), Avg (BSd ₂ ), Avg (BSd ₃ ), Avg (BSd ₄ ), Avg (BSd ₅ ), and Avg (BSd ₆ ).

Next, determine these differences Δ ₁ ~Δ _6. That is, Δ ₁ = (Avg (BS ₁ )-Avg (BSa ₁ )) + (Avg (BSd ₁ )-Avg (BS ₁ ))
Δ ₂ = (Avg (BS ₂ )-Avg (BSa ₂ )) + (Avg (BSd ₂ )-Avg (BS ₂ ))
Δ ₃ = (Avg (BS ₃ )-Avg (BSa ₃ )) + (Avg (BSd ₃ )-Avg (BS ₃ ))
Δ ₄ = (Avg (BS ₄ )-Avg (BSa ₄ )) + (Avg (BSd ₄ )-Avg (BS ₄ ))
Δ ₅ = (Avg (BS ₅ )-Avg (BSa ₅ )) + (Avg (BSd ₅ )-Avg (BS ₅ ))
Δ ₆ = (Avg (BS ₆ )-Avg (BSa ₆ )) + (Avg (BSd ₆ )-Avg (BS ₆ ))
Next, the parameter M having the largest value among Δ _{1 to} Δ ₆ and the subscript m of the M are specified. Ie
[M, m] = max (Δ ₁ , Δ ₂ , Δ ₃ , Δ ₄ , Δ ₅ , Δ ₆ )
It is.

Then, β _m is corrected by the following formula, and this is set as a new weight β _m .

_{{(Avg (BS m) -Avg} (BSa m)) + (Avg (BSd m) -Avg (BS m))} / Avg (BS m) * β m + β m → β m
Under “Subject Mode” and “Anger Mode”
{(Avg (BS _m ) -Avg (BSa _m )) + (Avg (BSd _m ) -Avg (BS _m ))} / Avg (BS _m ) * γ _m + γ _m → γ _m
Under “Subject Mode” and “Sad Mode”
{(Avg (BS _m ) -Avg (BSa _m )) + (Avg (BSd _m ) -Avg (SB _m ))} / Avg (BS _m ) * ω _m + ω _m → ω _m
Under “Subject Mode” and “Easy Mode”
{(Avg (BS _m ) -Avg (BSa _m )) + (Avg (BSd _m ) -Avg (BS _m ))} / Avg (BS _m ) * λ _m + λ _m → λ _m
In the case of the “photographer / subject mode”, both the same correction as the “photographer mode” and the same correction as the “subject mode” are performed.

  The weighting coefficient correction process can be repeated each time desired image data is added to a recommended image or desired image data is deleted from the recommended image. As a result, the image data close to the biometric information of the image data selected by the user as the recommended image is more easily selected as the recommended image, and the image data close to the biometric information of the image data not selected by the user as the recommended image becomes a more recommended image. It becomes difficult to be chosen.

  The recommended image classification process may be performed again after the end of the weighting coefficient correction process. Further, the recommended image classification process and the weight coefficient correction process may be repeated any number of times.

  The image data classified as the recommended image is presented to the user by the main control unit 501 as image data to be registered in a photo album or a folder. For example, in order to present recommended images, thumbnails of image data in folders classified as recommended images are displayed in a list on the display panel 521, or image data in folders classified as recommended images are sequentially displayed on the display panel 521. Control for preview display is performed by the main control unit 501.

  Although the examples of the present invention have been described above, the present invention is not limited to the above-described embodiments and modifications, and various modifications can be made without departing from the spirit of the present invention. For example, the wearable terminal 1 and the smartphone 500 may be integrally configured. Alternatively, the above processing may be performed by a personal computer or the like instead of the smartphone 500.

  Moreover, the classification of the recommended image is not limited to the active classification in which the image whose second evaluation value exceeds the threshold value is classified as the recommended image, the image whose second evaluation value does not exceed the threshold value is excluded, and the remaining images are excluded. A passive classification such as a recommended image may be used.

  Also, the emotion mode classification is not limited to the above, and any may be used as long as it can indicate the emotion, psychology, and mental state of the photographer or subject in accordance with the biological information.

  For example, relax, active, anxiety, excitement, startle, tension, indifference, stressful, sleep state, etc. may be classified as emotion modes. In addition, by defining weighting factors for biological information corresponding to these psychological states, the psychological state of the photographer or subject such as relaxed, active, anxiety, excitement, startle, tension, indifference, stressful, and dormant state The reflected correction value can be calculated with these weighting factors, the first evaluation value can be corrected with the correction value, and the second evaluation value can be calculated.

  For example, when the second evaluation value obtained by correcting the first evaluation value of the image data with the weight coefficient “relaxed” exceeds the threshold value corresponding to “relaxation”, the image data is changed to the recommended image in the “relaxation” mode. Classify.

  Alternatively, for example, all image data is classified into recommended images for the time being, and in “relaxation mode”, “anxiety”, “excitement”, “tension”, or “ When the second evaluation value obtained by correcting the first evaluation value of the image data with the weighting factor of “stressful” exceeds a threshold corresponding to “anxiety”, “excitement”, “tension”, or “stressful”, Exclude image data from the classification of recommended images in "Relax" mode. The first evaluation value here may be the psychological state of the subject that is grasped by analyzing the image data, such as the degree of smile. In this case, even if the smile level of the first evaluation value is high, if the second evaluation value with a specific gravity placed on the tension weighting factor is large, the subject of the image data is excluded from the recommended image because it is an unnatural smile. Can be done.

  As described above, the first evaluation value obtained from the image data is corrected by the photographer and the biological information of the subject acquired by the smartphone 500 from the wearable terminal 1 when photographing the image data, and various psychological states at the time of photographing are reflected. A second evaluation value can be obtained. Then, according to the second evaluation value, it is possible to classify and present recommended images according to the psychological state of the photographer and the subject at the time of photographing. Moreover, the weighting coefficient of the biometric information for correcting the first evaluation value can be corrected according to the addition or deletion of the recommended image by the user.

DESCRIPTION OF SYMBOLS 1 Wearable terminal 10 Display part 11 Display screen 12 Touch sensor 13 Fingerprint sensor 14 Operation button 500 Smartphone 501 Main control part 502 Case 510 Wireless communication part 520 Display input part 521 Display panel 522 Operation panel 530 Call part 531 Speaker 532 Microphone 540 Operation Unit 541 camera unit 542 projection unit 550 storage unit 551 internal storage unit 552 external storage unit 560 external input / output unit 570 GPS reception unit 580 motion sensor unit 590 power supply unit S1 first evaluation value calculation step S2 shooting mode determination step S3 photographer mode Weight setting step S4 Subject mode weight setting step S5 Photographer / subject mode weight setting step S6 Emotion mode discrimination step S7 Joy mode weight setting step S8 Angry mode weight setting step S9 Sad mode weight Setting step S10 Easy mode weight setting step S11 Biometric information acquisition and second evaluation value calculation step S12 Reference value setting and recommended image determination step S13 Recommended image classification step S21 Recommended image deletion determination step S22 Recommended image deletion step S23 Recommended image addition determination step S24 Recommended image addition step S25 Weight correction step

Claims (9)

An image information acquisition unit for acquiring image information;
A first evaluation value calculation unit for calculating a first evaluation value based on the image information;
A biological information acquisition unit that acquires biological information related to the image information;
The biological information , which includes at least one of a pulse, a respiratory rate, a body temperature, a sweat amount, and an electroencephalogram of the photographer and / or subject of the image information, and at least one temporal change amount thereof A correction value calculation unit that calculates a correction value of the first evaluation value based on an evaluation item ;
A second evaluation value calculator that calculates a second evaluation value of the image information by correcting the first evaluation value based on the correction value;
A correction value calculation mode setting unit for setting a mode for calculating the correction value;
A biometric information evaluation item weight setting unit that sets each weight corresponding to the biometric information evaluation item based on the set mode;
With
The correction value calculation unit, images evaluation device calculates the correction value based on a weight of each corresponding to the biological information evaluation items and the biological information evaluation items.   The first evaluation value calculation unit calculates at least one of image quality, resolution, characters, shooting date and time, shooting location, subject size, orientation, angle, and positional relationship between subjects in the image information. The image evaluation apparatus according to claim 1, wherein the first evaluation value is calculated based on the image information evaluation item included. The biological information evaluation item weight setting unit, according to claim 1, wherein the correction value calculation mode setting weight corresponding to the set mode by section, relatively set larger than the weight that does not correspond to the set mode Image evaluation device. The mode is a photographer mode in which a weight corresponding to the biometric information of the photographer of the image information is set to be relatively larger than a weight corresponding to the biometric information of the subject of the image information, and the biometric of the photographer of the image information A subject mode in which a weight corresponding to the biological information of the subject of the image information is set to be relatively larger than a weight corresponding to the information; and a weight corresponding to the biological information of the photographer of the image information and the subject of the image information The image evaluation apparatus according to claim 3 , wherein the image evaluation apparatus includes any one of photographer subject modes in which weights corresponding to biometric information are set equally. The mode is an emotion for setting each weight corresponding to the biometric information evaluation item based on one emotion arbitrarily selected from emotions of the photographer and / or the subject of the image information. the image evaluation apparatus according to any one of claims 1 to 4 including the selection mode. An image information acquisition unit for acquiring image information;
A first evaluation value calculation unit for calculating a first evaluation value based on the image information;
A biological information acquisition unit that acquires biological information related to the image information;
The biological information, which includes at least one of a pulse, a respiratory rate, a body temperature, a sweat amount, and an electroencephalogram of the photographer and / or subject of the image information, and at least one temporal change amount thereof A correction value calculation unit that calculates a correction value of the first evaluation value based on an evaluation item;
A second evaluation value calculator that calculates a second evaluation value of the image information by correcting the first evaluation value based on the correction value;
An evaluation reference value setting unit for setting an evaluation reference value serving as a reference for recommending the image information;
A recommended image classification determination unit that determines whether to classify the image information into recommended images based on the second evaluation value and the evaluation reference value;
A recommended image classification unit that classifies the image information into recommended images according to the determination result;
With
The recommended image classification unit classifies one or more pieces of image information arbitrarily designated by a user operation into recommended images,
On the basis of the biological information evaluation items corresponding to the classified one or more recommended image based on a user's operation, each weight correcting unit images evaluation device Ru with a for correcting the weight of the biological information evaluation items. An image information acquisition unit for acquiring image information;
A first evaluation value calculation unit for calculating a first evaluation value based on the image information;
A biological information acquisition unit that acquires biological information related to the image information;
The biological information, which includes at least one of a pulse, a respiratory rate, a body temperature, a sweat amount, and an electroencephalogram of the photographer and / or subject of the image information, and at least one temporal change amount thereof A correction value calculation unit that calculates a correction value of the first evaluation value based on an evaluation item;
A second evaluation value calculator that calculates a second evaluation value of the image information by correcting the first evaluation value based on the correction value;
An evaluation reference value setting unit for setting an evaluation reference value serving as a reference for recommending the image information;
A recommended image classification determination unit that determines whether to classify the image information into recommended images based on the second evaluation value and the evaluation reference value;
A recommended image classification unit that classifies the image information into recommended images according to the determination result;
With
The recommended image classification unit excludes one or more pieces of image information arbitrarily designated by a user operation from the recommended image,
Based on the biological information evaluation items corresponding to one or a plurality of image information are excluded from the recommendation image based on the user operation, images of Ru with a weight corrector for correcting the weights of each of the biological information evaluation items Evaluation device. Computer
Obtaining image information;
Calculating a first evaluation value based on the image information;
Obtaining biological information related to the image information;
The biological information , which includes at least one of a pulse, a respiratory rate, a body temperature, a sweat amount, and an electroencephalogram of the photographer and / or subject of the image information, and at least one temporal change amount thereof Calculating a correction value of the first evaluation value based on an evaluation item ;
Calculating the second evaluation value of the image information by correcting the first evaluation value based on the correction value;
Setting a mode for calculating the correction value;
Setting each weight corresponding to the biometric information evaluation item based on the set mode;
Perform image evaluation method. An image evaluation program for causing a computer to execute the image evaluation method according to claim 8 .

Images