CN112347832A - Unlocking method, device and equipment based on face recognition and computer storage medium - Google Patents
Unlocking method, device and equipment based on face recognition and computer storage medium Download PDFInfo
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Abstract
The invention discloses an unlocking method, a device, equipment and a computer storage medium based on face recognition, wherein the method comprises the following steps: acquiring video information sent by the preset acquisition equipment, wherein the video information comprises standard video information and video information to be identified; when the standard video information comprises a standard face image, processing the standard face image to obtain a standard texture feature of the standard face image, and updating and storing the standard texture feature to a preset database; when the video information to be recognized comprises a face image to be recognized, acquiring texture features to be recognized of the face image to be recognized; and comparing the texture features to be identified with each pre-stored standard texture feature in a preset database, and executing an unlocking instruction when a target standard texture feature matched with the texture features to be identified exists in the preset database. The invention improves the unlocking accuracy based on face recognition.
Description
Technical Field
The invention relates to the field of monitoring of the Internet of things, in particular to an unlocking method, an unlocking device, unlocking equipment and a computer storage medium based on face recognition.
Background
With the continuous maturity of the internet of things technology, smart homes are rapidly developed, and more families use smart door locks capable of being incorporated into the internet of things.
The existing intelligent door lock is realized through fingerprint identification or face identification, fingerprint information of a user needs to be collected through fingerprint identification, the step of opening and closing a door by using a traditional key is only saved for the fingerprint identification intelligent door lock, real liberation of both hands cannot be achieved, and complete liberation of both hands is achieved through face identification.
Disclosure of Invention
The invention mainly aims to provide an unlocking method based on face recognition, and aims to solve the technical problems that in the prior art, the intelligent door lock based on face recognition is complex in data processing and the recognition accuracy rate cannot be guaranteed.
In addition, in order to achieve the purpose, the invention also provides an unlocking method based on face recognition, the unlocking method based on face recognition is applied to an intelligent household platform, and the intelligent household platform is in communication connection with a door lock and at least two preset acquisition devices;
the unlocking method based on the face recognition comprises the following steps:
acquiring video information sent by preset acquisition equipment, wherein the video information comprises standard video information and video information to be identified;
when the standard video information comprises a standard face image, processing the standard face image to obtain a standard texture feature of the standard face image, and updating and storing the standard texture feature to a preset database;
when the video information to be recognized comprises a face image to be recognized, acquiring texture features to be recognized of the face image to be recognized;
and comparing the texture features to be identified with each pre-stored standard texture feature in a preset database, and executing an unlocking instruction when a target standard texture feature matched with the texture features to be identified exists in the preset database.
Optionally, before the step of obtaining the video information sent by the preset acquisition device, the method includes:
acquiring the equipment type and the equipment position information of the preset acquisition equipment;
dividing the preset acquisition equipment into first type acquisition equipment and second type acquisition equipment according to respective equipment types and equipment position information;
acquiring video information sent by the preset acquisition equipment and an equipment identifier associated with the video information;
if the equipment identification is the first equipment identification of the first type of acquisition equipment, dividing the video information into standard video information;
and if the equipment identifier is a second equipment identifier of the second type of acquisition equipment, dividing the video information into video information to be identified.
Optionally, when the video information to be recognized includes a face image to be recognized, the step of obtaining the texture feature to be recognized of the face image to be recognized includes:
when the video information to be recognized comprises face images to be recognized, determining the number of devices for acquiring the face images to be recognized;
determining the size of a feature map according to the number of the devices, and extracting feature pixel points from the face image to be recognized according to the size of the feature map;
and converting the characteristic pixel points into binary pixel characteristic operator values, and representing the pixel characteristic operator values as the texture characteristics to be recognized of the face image to be recognized.
Optionally, when a target standard texture feature matching the texture feature to be identified exists in the preset database, the step of executing an unlocking instruction includes:
when a target standard texture feature matched with the texture feature to be identified exists in the preset database, inquiring whether a new access device exists;
if the new access equipment exists, acquiring the equipment identifier of the new access equipment, and judging whether the equipment identifier of the new access equipment is preset or not;
and if the equipment identifier of the new access equipment is the preset equipment identifier, executing an unlocking instruction.
Optionally, after the step of executing the unlocking instruction if the device identifier of the new access device is the preset device identifier, the method includes:
if the equipment identifier of the new access equipment is a preset equipment identifier, acquiring user behavior data in the new access equipment;
inquiring a preset user database, and acquiring historical behavior data associated with the equipment identifier of the new access equipment;
comparing the user behavior data with the historical behavior data to obtain new behavior data, and updating and storing the new behavior data to the preset user database;
and determining a target unlocking mode according to the data volume of the newly added behavior data, and adjusting the unlocking mode door lock corresponding to the equipment identifier of the newly accessed equipment to the target unlocking mode.
Optionally, the step of determining a target unlocking mode according to the data volume of the newly added behavior data, and adjusting the unlocking mode door lock corresponding to the device identifier of the newly accessed device to the target unlocking mode includes:
if the data volume of the newly added behavior data is larger than or equal to a first preset volume, determining that the target unlocking mode is a child mode, and reducing the unlocking force of the door handle;
if the data volume of the newly added behavior data is smaller than a first preset volume and larger than a second preset volume, determining that the target unlocking mode is a youth mode, and increasing the door handle unlocking force;
and if the data volume of the newly-added behavior data is less than or equal to a second preset volume, determining that the target unlocking mode is an old-age mode, and setting the target unlocking mode as the normal door handle unlocking force.
Optionally, after the step of obtaining the video information sent by the preset acquisition device, the method further includes:
analyzing each video picture in the standard video information and/or the video information to be identified;
if a moving object exists in the standard video information and/or the video information to be identified, acquiring an outer edge outline of the moving object;
and if the outer edge contour is a human body contour, judging that the standard video information and/or the video information to be identified comprise a human face image.
In addition, in order to achieve the above object, the present invention further provides an unlocking apparatus based on face recognition, including:
the acquisition and division module is used for acquiring the video information sent by the preset acquisition equipment and dividing the video information into video information to be identified and standard video information;
the first processing module is used for acquiring texture features to be recognized of the face image to be recognized when the video information to be recognized comprises the face image to be recognized;
the second processing module is used for processing the standard face image to obtain the standard texture features of the standard face image when the standard video information comprises the standard face image, and updating and storing the standard texture features to a preset database;
and the instruction execution module is used for comparing the texture features to be identified with each pre-stored standard texture feature in a preset database, and executing an unlocking instruction when a target standard texture feature matched with the texture features to be identified exists in the preset database.
In addition, in order to achieve the above object, the present invention further provides an unlocking apparatus based on face recognition, including: the unlocking method comprises a memory, a processor and an unlocking program based on the face recognition, wherein the unlocking program based on the face recognition is stored in the memory and can run on the processor, and when the unlocking program based on the face recognition is executed by the processor, the steps of the unlocking method based on the face recognition are realized.
In addition, in order to achieve the above object, the present invention further provides a computer storage medium, where an unlocking program based on face recognition is stored, and when the unlocking program based on face recognition is executed by a processor, the steps of the unlocking method based on face recognition are implemented.
The embodiment of the invention provides an unlocking method, an unlocking device, unlocking equipment and a readable storage medium based on face recognition. The method comprises the steps that a plurality of preset acquisition devices are arranged, video information sent by the preset acquisition devices is obtained, and the video information comprises standard video information and video information to be identified; when the standard video information comprises a standard face image, acquiring standard texture features of the standard face image, and updating and storing the standard texture features to a preset database; when the video information to be recognized comprises a face image to be recognized, acquiring texture features to be recognized of the face image to be recognized; will treat discernment textural feature and the standard textural feature that each prestores in predetermineeing the database compare exist in predetermineeing the database with when treating the target standard textural feature that discernment textural feature matches, carry out the instruction of unblanking, do not need the manual update of user's regular or unscheduled to prestore standard face information in this embodiment, accomplished the real-time update of standard face information in predetermineeing the database, make face image abundanter when having reduced user operation, simultaneously through simple video information processing, just can realize accurate face identification, when reducing the data processing degree of difficulty, guaranteed the face identification rate of accuracy to the accuracy of unblanking has been improved.
Drawings
Fig. 1 is a schematic diagram of a hardware structure of an implementation manner of an unlocking device based on face recognition according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of an unlocking method based on face recognition according to the present invention;
fig. 3 is a schematic view of functional modules of an embodiment of the unlocking device based on face recognition.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.
The unlocking terminal (called terminal, equipment or terminal equipment) based on face recognition in the embodiment of the invention can be a PC (personal computer), and can also be a mobile terminal equipment with a display function, such as a smart phone, a tablet personal computer and a portable computer.
As shown in fig. 1, the terminal may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the terminal may further include a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WiFi module, and the like. Such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that may adjust the brightness of the display screen according to the brightness of ambient light, and a proximity sensor that may turn off the display screen and/or the backlight when the mobile terminal is moved to the ear. As one of the motion sensors, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally, three axes), detect the magnitude and direction of gravity when the mobile terminal is stationary, and can be used for applications (such as horizontal and vertical screen switching, related games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer and tapping) and the like for recognizing the attitude of the mobile terminal; of course, the mobile terminal may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which are not described herein again.
Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and an unlocking program based on face recognition.
In the terminal shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to invoke the unlocking program based on the face recognition stored in the memory 1005, and when the unlocking program based on the face recognition is executed by the processor, the processor implements the operations in the unlocking method based on the face recognition provided in the following embodiments.
Based on the hardware structure of the equipment, the embodiment of the unlocking method based on the face recognition is provided.
Referring to fig. 2, in a first embodiment of the unlocking method based on face recognition, the unlocking method based on face recognition includes:
and step S10, acquiring video information sent by preset acquisition equipment, wherein the video information comprises standard video information and video information to be identified.
In this embodiment, the unlocking method based on face recognition is applied to an intelligent home platform, the intelligent home platform acquires video information sent by preset acquisition equipment, the video information includes standard video information and video information to be recognized, that is, an equipment identifier associated with the video information of the intelligent home platform, and the intelligent home platform divides the video information into the video information to be recognized and the standard video information according to the equipment identifier associated with the video information (the equipment identifier uniquely identifies the identification information of the equipment, for example, the equipment name), specifically:
intelligence house platform and lock and at least two preset collection equipment communication connection, preset collection equipment can be cell-phone, bracelet and/or lock camera device, and intelligent house platform will preset collection equipment and divide into two types, specifically:
acquiring the equipment type and the equipment position information of the preset acquisition equipment;
and dividing the preset acquisition equipment into first-class acquisition equipment and second-class acquisition equipment according to respective equipment types and equipment position information.
Acquiring video information sent by the preset acquisition equipment and an equipment identifier associated with the video information;
if the equipment identification is the first equipment identification of the first type of acquisition equipment, dividing the video information into standard video information;
and if the equipment identification is a second equipment identification of second-class acquisition equipment, dividing the video information into video information to be identified.
The intelligent home platform acquires the equipment type and the equipment position information of preset acquisition equipment, and divides the preset acquisition equipment into first-class acquisition equipment and second-class acquisition equipment according to the equipment type and the equipment position information of the preset acquisition equipment; that is, the intelligent home platform uses an indoor camera which is installed in the room and collects a standard face image (the standard face image refers to a family face image) as a first type of device, and uses an outdoor walkway or a doorbell which is installed in the room and collects a camera which collects a face image to be recognized (the face image to be recognized refers to a visitor face image and/or a family face image) as a second type of device. The preset acquisition equipment can be a mobile phone, a bracelet and the like, and the positions of the mobile phone and the bracelet can move, so that the intelligent home platform can accurately classify the equipment according to the equipment type and the equipment position information of the preset acquisition equipment.
In this embodiment, the preset acquisition devices are divided into two types, so as to process video information from different sources respectively, and improve the accuracy of face recognition, that is, the intelligent home platform uses the video information acquired by the first type of acquisition device as standard video information, the intelligent home platform uses the video information acquired by the second type of acquisition device as to-be-recognized video information, the intelligent home platform extracts a standard face image from the standard video information, the intelligent home platform processes the standard face image to obtain a standard texture feature of the standard face image, updates and stores the standard texture feature into a preset database as pre-stored face information, the intelligent home platform compares the to-be-recognized face information with the pre-stored face information from the to-be-recognized video information acquired by the second type of acquisition device, so as to realize accurate recognition, and perform unlocking operation, specifically:
and step S20, when the standard video information comprises a standard face image, processing the standard face image to obtain the standard texture feature of the standard face image, and updating and storing the standard texture feature to a preset database.
When the standard video information of the intelligent home platform comprises a standard face image, the intelligent home platform processes the standard face image to obtain standard texture characteristics of the standard face image; and the intelligent home platform updates and stores the standard texture characteristics to a preset database.
The intelligent home platform updates and saves the standard texture features to a preset database, and the method comprises the following steps:
the first method is as follows: the intelligent home platform directly supplements the standard texture features into a preset database, for example, newly added family members in xx families or newly added expressions of existing family members in xxx families, namely, the intelligent home platform acquires standard video image information containing a standard facial image, the intelligent home platform processes the standard facial image to obtain the standard texture features of the standard facial image, and the intelligent home platform directly stores the standard texture features into the preset database; when a new member is added in a family, a user does not need to actively input, and automatic acquisition and updating of the standard texture features in the preset database are realized, so that the user operation is more convenient.
The second method comprises the following steps: the intelligent home furnishing platform replaces the standard texture characteristics with the standard texture characteristics stored in the preset database in a one-to-one correspondence manner, that is, the intelligent home furnishing platform compares the collected standard texture features with standard texture features already stored in a preset database to obtain target standard texture features with highest similarity to the collected standard texture features in the preset database, the intelligent home furnishing platform replaces the collected standard texture features and the target standard texture features to store the same in the preset database, for example, the xxx family members have undergone micro-shaping on their faces, the smart home platform saves the latest standard texture features, in this way, the standard texture features contained in the preset database are real-time information, and the amount of information is minimal, when the face is compared and identified, the face can be compared efficiently and accurately, and the efficiency and the accuracy of face identification are ensured.
It can be understood that in the practical use, the intelligent home platform combines the two modes, so that the richness of facial image expressions is guaranteed, the minimum data volume can be guaranteed, and the facial comparison can be conveniently, efficiently and accurately carried out.
Specifically, when the video information to be recognized includes the face image to be recognized in step S20, the step of obtaining the texture feature to be recognized of the face image to be recognized includes:
step a1, when the standard video information comprises standard face images, determining the number of devices for acquiring the standard face images;
step a2, determining the size of a feature map according to the number of the devices, and extracting feature pixel points from the standard face image according to the size of the feature map;
step a3, converting the characteristic pixel points into binary pixel characteristic operator values, and representing the standard texture characteristics of the standard face image by the pixel characteristic operator values.
The intelligent home platform comprises a standard face image in the standard video information, processes the standard face image and generates standard texture characteristics representing the standard face image. That is, the standard video information that intelligent home platform gathered in this embodiment is the video information of people at home, intelligent home platform gathers facial image from each angle, can make the standard texture feature that generates more accurate, simultaneously intelligent home platform gathers standard video information in real time, extract standard texture feature according to standard video information, the real-time update of standard face information in the preset database has been done, do not need the user regularly or the manual update of unscheduled standard face information that prestores, in this embodiment the real-time of standard information is guaranteed effectively when having reduced user operation, thereby improve the accuracy that the people's face compared.
In step S20 and step S30 of this embodiment, the smart home platform determines the size of the feature map according to the number of devices, and extracts a small number of image features, so that when the data processing amount is small, the image processing effect can still be ensured, and thus, the accuracy of image processing can still be ensured under the condition that the requirement on the hardware performance of the smart home platform is low.
Step S30, when the video information to be recognized includes the face image to be recognized, the texture feature to be recognized of the face image to be recognized is obtained.
When the intelligent home platform detects that the video information to be recognized comprises the face image to be recognized, the intelligent home platform processes the face image to be recognized to obtain the texture feature to be recognized of the face image to be recognized, specifically, the step of refining of the step S30 includes:
b1, when the video information to be recognized comprises the face images to be recognized, determining the number of the devices for collecting the face images to be recognized;
b2, determining the size of a feature map according to the number of the devices, and extracting feature pixel points from the face image to be recognized according to the size of the feature map;
step b3, converting the characteristic pixel points into binary pixel characteristic operator values, and representing the texture characteristics to be recognized of the face image to be recognized by the pixel characteristic operator values.
For example, the equipment that the intelligent home platform confirmed to gather the face image of waiting to discern is 3 for corridor camera, face identification camera and doorbell camera, then intelligent home platform developments set for the characteristic diagram size to be: the number of horizontal pixels is 3 times 3 kinds of pixels, and the number of vertical pixels is 3 times 3 kinds of pixels, for example: (3 × 3) ((3 × 3)), the smart home platform takes the central pixel of the feature map as a threshold, compares the adjacent gray value of 1 pixel with the threshold, if the peripheral pixel value is greater than or equal to the central pixel value, the position of the pixel is marked as 1, otherwise, the position is 0. Thus, 27 points in the neighborhood of (3 × 3) ((3 × 3)) can generate 27-bit binary numbers (usually converted into decimal numbers, namely feature pixel codes, 134217728 types), that is, pixel feature operator values of the central pixel points of the feature map are obtained, and the intelligent home platform reflects the texture features to be recognized of the face image to be recognized by using the values.
In the embodiment of the present invention, the sequence between step S20 and step S30 is not specifically limited, that is, the smart home platform may update and store the standard texture features to the preset database, or may perform the standard texture features simultaneously, or may obtain the texture features to be recognized of the face image to be recognized, and the two steps may be implemented independently.
And step S40, comparing the textural features to be identified with each pre-stored standard textural feature in a preset database, and executing an unlocking instruction when target standard textural features matched with the textural features to be identified exist in the preset database.
In this embodiment, when the smart home platform compares the texture features to be identified with the pre-stored standard texture features in the preset database, the preset database is updated (the standard texture features are updated and stored in the preset database) with at least one standard texture feature. Namely, the difference between the embodiment and the prior art is that the smart home platform compares the texture to be recognized with the updated standard texture features in the preset database formed by automatic updating, and the standard texture features in the preset database are ensured to be real-time and accurate, so that the accuracy of image recognition is ensured; the intelligent home platform compares the texture features to be recognized with the pre-stored standard texture features in the preset database, when the target standard texture features matched with the texture features to be recognized exist in the preset database, the intelligent home platform judges that the face images to be recognized collected outdoors are matched with the standard face images collected indoors, the intelligent home platform controls the door lock to execute the unlocking instruction, namely, the intelligent home platform judges that the face images to be recognized collected outdoors are matched with the standard face images collected indoors, and the intelligent home platform controls the door lock to execute the unlocking instruction.
In the embodiment, a plurality of preset acquisition devices are arranged, video information sent by the preset acquisition devices is obtained, and the video information is divided into video information to be identified and standard video information; when the video information to be recognized comprises a face image to be recognized, acquiring texture features to be recognized of the face image to be recognized; when the standard video information comprises a standard face image, acquiring standard texture features of the standard face image, and updating and storing the standard texture features to a preset database; will treat discernment textural feature and the standard textural feature that each prestores in predetermineeing the database compare exist in predetermineeing the database with when treating the target standard textural feature that discernment textural feature matches, carry out the instruction of unblanking, do not need the manual update of user's regular or unscheduled to prestore standard face information in this embodiment, accomplished the real-time update of standard face information in predetermineeing the database, make face image abundanter when having reduced user operation, simultaneously through simple video information processing, just can realize accurate face identification, when reducing the data processing degree of difficulty, guaranteed the face identification rate of accuracy to the accuracy of unblanking has been improved.
Further, on the basis of the above embodiment of the present invention, a second embodiment of the unlocking method based on face recognition is provided.
This embodiment is a refinement of step S40 in the first embodiment, and is different from the above-described embodiments of the present invention in that:
when a target standard texture feature matched with the texture feature to be identified exists in the preset database, inquiring whether a new access device exists;
if the new access equipment exists, acquiring the equipment identifier of the new access equipment, and judging whether the equipment identifier of the new access equipment is preset or not;
and if the equipment identifier of the new access equipment is the preset equipment identifier, executing an unlocking instruction.
When the target standard texture features matched with the texture features to be recognized exist in the preset database, namely, the intelligent home platform determines that the target standard texture features are the same person, but due to the fact that the phenomenon of twins exists, in order to avoid the unlocking situation, the intelligent home platform inquires whether new access equipment exists or not; if the new access equipment exists, the intelligent home platform acquires the equipment identifier of the new access equipment, and judges whether the equipment identifier of the new access equipment is preset equipment identifier or not (the preset equipment identifier refers to the equipment identifier of family members prestored in the intelligent home platform); and if the equipment identifier of the newly accessed equipment is the preset equipment identifier, the intelligent household platform controls the door lock to execute an unlocking instruction. The unlocking mode corresponding to the equipment identification of the new access equipment is utilized for unlocking in the embodiment, so that the switch of the door lock is more intelligent.
The intelligent home platform all has wireless network in this embodiment, and the people can connect wireless network at home under the general condition, and wireless network has the memory function, and when the people was close to home, just can realize wireless network's automatic connection, and face identification and new network access equipment simultaneous analysis are avoided the condition that the mistake was unblanked in this embodiment, have further improved the accuracy of unblanking.
Further, on the basis of the above embodiment of the present invention, a third embodiment of the unlocking method based on face recognition is provided.
This embodiment is a step after the second embodiment, and the difference between this embodiment and the above embodiment of the present invention is:
and if the equipment identifier of the new access equipment is a preset equipment identifier, acquiring user behavior data in the new access equipment.
Inquiring a preset user database, and acquiring historical behavior data associated with the equipment identifier of the new access equipment;
comparing the user behavior data with the historical behavior data to obtain newly added behavior data;
and determining a target unlocking mode according to the data volume of the newly added behavior data, and adjusting the unlocking mode door lock corresponding to the equipment identifier of the newly accessed equipment to the target unlocking mode.
When the intelligent home platform inquires the new access device, unlocking by using a target unlocking mode (obtained by adjusting the unlocking mode corresponding to the device identifier of the new access device) corresponding to the device identifier of the new access device, and if the device identifier of the new access device is a preset device identifier, acquiring user behavior data in the new access device by the intelligent home platform. The intelligent home platform inquires a preset user database (historical user behavior data of the newly accessed equipment is stored in the preset user database), and the intelligent home platform acquires the historical behavior data associated with the equipment identifier of the newly accessed equipment; the intelligent home platform compares the user behavior data with historical behavior data to obtain newly added behavior data; the intelligent home platform determines a target unlocking mode according to the data volume of the newly-added behavior data, and adjusts an unlocking mode door lock corresponding to the equipment identifier of the newly-accessed equipment to the target unlocking mode; specifically, the method comprises the following steps:
if the data volume of the newly-added behavior data is larger than or equal to a first preset volume, determining that the target unlocking mode is a child mode, and reducing the unlocking force of the door handle;
if the data volume of the newly added behavior data is smaller than a first preset volume and larger than a second preset volume, determining that the target unlocking mode is a youth mode, and increasing the door handle unlocking force;
and if the data volume of the newly-added behavior data is less than or equal to a second preset volume, determining that the target unlocking mode is an old-age mode, and setting the target unlocking mode as the normal door handle unlocking force.
If the data volume of the newly added behavior data is greater than or equal to a first preset volume (the first preset volume can be set according to a specific scene, for example, the first preset volume is set to be 200M), the intelligent home platform determines that an unlocking mode corresponding to the device identifier of the newly accessed device is a child mode, and the intelligent home platform controls to reduce the door handle unlocking force; the child can conveniently unlock the lock.
If the data volume of the newly added behavior data is smaller than a first preset volume and larger than a second preset volume (the second preset volume can be set according to a specific scene, for example, the second preset volume is set to be 100M), the intelligent home platform determines that the unlocking mode corresponding to the device identifier of the newly accessed device is a youth mode, and increases the door handle unlocking force; the labor waste of adults is reduced, and the work done by the adults is reserved to be consumed in a child mode.
And if the data volume of the newly-added behavior data is less than or equal to a second preset volume, the intelligent home platform determines that the unlocking mode corresponding to the equipment identifier of the newly-accessed equipment is the old mode, and sets the unlocking mode as the normal door handle unlocking force.
The intelligent house platform confirms the identity information of the person who unblanks according to the user action data increase volume of access device among this example to control door handle power of unblanking, make the operation of unblanking more convenient, promptly, the unnecessary hard of young mode can be gathered to the intelligent house platform, uses at children's mode, makes things convenient for the user operation at different age stages. In addition, it can be understood that, in this embodiment, the unlocking mode is set according to the data volume of the new added behavior data in the device, and in the actual use process, the smart home platform may also determine the unlocking mode according to the device identifier or the use information of the application software in the device, which is not described in detail in this embodiment.
Further, on the basis of the above embodiment of the present invention, a fourth embodiment of the unlocking method based on face recognition is provided.
This embodiment is a step after step S10 in the first embodiment, and the present embodiment is different from the above-described embodiments of the present invention in that:
analyzing each video picture in the standard video information and/or the video information to be identified;
if a moving object exists in the standard video information and/or the video information to be identified, acquiring an outer edge outline of the moving object;
and if the outer edge contour is a human body contour, judging that the standard video information and/or the video information to be identified comprise a human face image.
In the embodiment, the intelligent home platform analyzes each video picture in the standard video information and/or the video information to be identified; the intelligent home platform compares each standard video picture in the standard video information to determine whether a moving object exists in the standard video pictures, and if the moving object exists in the standard video information and/or the video information to be identified, the outer edge outline of the moving object is obtained; the intelligent home platform judges whether the outer edge profile is a human body profile, and if the outer edge profile is the human body profile, the intelligent home platform judges that the standard video information and/or the video information to be identified comprise a human face image. In the implementation, the needle analyzes the video information to determine whether the video information comprises the face image, and when the video information comprises the face image, the face image is analyzed to obtain the texture characteristics corresponding to the face image, so that the texture characteristics are compared to perform accurate identity recognition, thereby realizing unlocking operation.
It is understood that the method of the above embodiments can be clearly understood by those skilled in the art, and one or more embodiments can be arbitrarily selected from the second to the third embodiments to be combined with the technical solution of the first embodiment.
In addition, referring to fig. 3, an embodiment of the present invention further provides an unlocking device based on face recognition, where the unlocking device based on face recognition includes:
the acquiring and dividing module 10 is configured to acquire video information sent by the preset acquisition device, and divide the video information into video information to be identified and standard video information;
the first processing module 20 is configured to, when the video information to be recognized includes a face image to be recognized, obtain a texture feature to be recognized of the face image to be recognized;
the second processing module 30 is configured to, when the standard video information includes a standard face image, process the standard face image to obtain a standard texture feature of the standard face image, and update and store the standard texture feature to a preset database;
and the instruction execution module 40 is configured to compare the texture features to be identified with each pre-stored standard texture feature in a preset database, and execute an unlocking instruction when a target standard texture feature matching the texture features to be identified exists in the preset database.
In one embodiment, the unlocking device based on face recognition includes:
the information acquisition module is used for acquiring the equipment type and the equipment position information of the preset acquisition equipment;
the device classification module is used for dividing the preset acquisition devices into a first type of acquisition devices and a second type of acquisition devices according to respective device types and device position information;
the acquiring and dividing module 10 includes:
the information acquisition unit is used for acquiring the video information sent by the preset acquisition equipment and the equipment identification related to the video information;
the first dividing unit is used for dividing the video information into standard video information if the equipment identification is the first equipment identification of the first type of acquisition equipment;
and the second dividing unit is used for dividing the video information into the video information to be identified if the equipment identifier is a second equipment identifier of the second type of acquisition equipment.
In an embodiment, the first processing module 20 includes:
the quantity determining unit is used for determining the quantity of the equipment for acquiring the facial images to be recognized when the video information to be recognized comprises the facial images to be recognized;
the pixel extraction unit is used for determining the size of a feature map according to the number of the devices and extracting feature pixel points from the face image to be recognized according to the size of the feature map;
and the feature processing unit is used for converting the feature pixel points into binary pixel feature operator values and representing the texture features to be recognized of the face image to be recognized by the pixel feature operator values.
In one embodiment, the instruction execution module includes:
the matching query unit is used for querying whether new access equipment exists or not when the target standard texture features matched with the texture features to be identified exist in the preset database;
the identification judgment unit is used for acquiring the equipment identification of the new access equipment if the new access equipment exists and judging whether the equipment identification of the new access equipment is preset or not;
and the instruction execution unit is used for executing an unlocking instruction if the equipment identifier of the new access equipment is a preset equipment identifier.
In one embodiment, the unlocking device based on face recognition includes:
the data acquisition module is used for acquiring user behavior data in the new access equipment if the equipment identifier of the new access equipment is a preset equipment identifier;
the query acquisition module is used for querying a preset user database and acquiring historical behavior data associated with the equipment identifier of the new access equipment;
the data comparison module is used for comparing the user behavior data with the historical behavior data to obtain newly added behavior data;
and the mode adjusting module is used for determining a target unlocking mode according to the data volume of the newly added behavior data and adjusting the unlocking mode door lock corresponding to the equipment identifier of the newly accessed equipment to the target unlocking mode.
The mode adjustment module 30 includes:
the first determining unit is used for determining that the target unlocking mode is a child mode and reducing the unlocking force of the door handle if the data volume of the newly added behavior data is larger than or equal to a first preset volume;
the second determining unit is used for determining that the target unlocking mode is a youth mode and increasing the unlocking force of the door handle if the data volume of the newly added behavior data is smaller than a first preset volume and larger than a second preset volume;
and the third determining unit is used for determining that the target unlocking mode is the old mode and setting the target unlocking mode as the normal door handle unlocking force if the data volume of the newly added behavior data is less than or equal to a second preset volume.
In one embodiment, the unlocking device based on face recognition includes:
the picture comparison module is used for analyzing each video picture in the standard video information and/or the video information to be identified;
the outline determining module is used for acquiring the outline of the outer edge of the moving object if the standard video information and/or the video information to be identified has the moving object;
and the face recognition module is used for judging that the standard video information and/or the video information to be recognized comprise face images if the outer edge contour is a human body contour.
The method executed by each program module can refer to each embodiment of the method of the present invention, and is not described herein again.
The embodiment of the invention is provided with a plurality of preset acquisition devices, video information acquired by the preset acquisition devices is divided into video information to be recognized and standard video information, texture features to be recognized and standard texture features are determined according to the video information to be recognized and the standard video information, and an unlocking instruction is executed when the texture features to be recognized are matched with the standard texture features.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a tablet computer, etc.) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An unlocking method based on face recognition is characterized by comprising the following steps:
acquiring video information sent by preset acquisition equipment, wherein the video information comprises standard video information and video information to be identified;
when the standard video information comprises a standard face image, processing the standard face image to obtain a standard texture feature of the standard face image, and updating and storing the standard texture feature to a preset database;
when the video information to be recognized comprises a face image to be recognized, acquiring texture features to be recognized of the face image to be recognized;
and comparing the texture features to be identified with each pre-stored standard texture feature in a preset database, and executing an unlocking instruction when a target standard texture feature matched with the texture features to be identified exists in the preset database.
2. The unlocking method based on face recognition as claimed in claim 1, wherein the obtaining of the video information sent by the preset acquisition device includes:
acquiring the equipment type and the equipment position information of the preset acquisition equipment;
dividing the preset acquisition equipment into first type acquisition equipment and second type acquisition equipment according to respective equipment types and equipment position information;
acquiring video information sent by the preset acquisition equipment and equipment identification related to the video information;
if the equipment identification is the first equipment identification of the first type of acquisition equipment, dividing the video information into standard video information;
and if the equipment identifier is a second equipment identifier of the second type of acquisition equipment, dividing the video information into video information to be identified.
3. The unlocking method based on face recognition according to claim 1, wherein the step of obtaining the texture features to be recognized of the face image to be recognized when the video information to be recognized includes the face image to be recognized includes:
when the video information to be recognized comprises face images to be recognized, determining the number of devices for acquiring the face images to be recognized;
determining the size of a feature map according to the number of the devices, and extracting feature pixel points from the face image to be recognized according to the size of the feature map;
and converting the characteristic pixel points into binary pixel characteristic operator values, and representing the pixel characteristic operator values as the texture characteristics to be recognized of the face image to be recognized.
4. The unlocking method based on the face recognition as claimed in claim 1, wherein the step of executing the unlocking instruction when the target standard texture feature matching with the texture feature to be recognized exists in the preset database comprises:
when a target standard texture feature matched with the texture feature to be identified exists in the preset database, inquiring whether a new access device exists;
if the new access equipment exists, acquiring the equipment identifier of the new access equipment, and judging whether the equipment identifier of the new access equipment is a preset equipment identifier or not;
and if the equipment identifier of the new access equipment is the preset equipment identifier, executing an unlocking instruction.
5. The unlocking method based on face recognition according to claim 4, wherein after the step of executing the unlocking instruction if the device identifier of the newly accessed device is the preset device identifier, the method comprises:
if the equipment identifier of the new access equipment is a preset equipment identifier, acquiring user behavior data in the new access equipment;
inquiring a preset user database, and acquiring historical behavior data associated with the equipment identifier of the new access equipment;
comparing the user behavior data with the historical behavior data to obtain new behavior data, and updating and storing the new behavior data to the preset user database;
and determining a target unlocking mode according to the data volume of the newly added behavior data, and adjusting the unlocking mode corresponding to the equipment identifier of the newly accessed equipment to the target unlocking mode.
6. The unlocking method based on face recognition according to claim 5, wherein the step of determining a target unlocking mode according to the data volume of the new behavior data and adjusting the unlocking mode corresponding to the device identifier of the new access device to the target unlocking mode includes:
if the data volume of the newly added behavior data is larger than or equal to a first preset volume, determining that the target unlocking mode is a child mode, and reducing the unlocking force of the door handle;
if the data volume of the newly added behavior data is smaller than a first preset volume and larger than a second preset volume, determining that the target unlocking mode is a youth mode, and increasing the door handle unlocking force;
and if the data volume of the newly-added behavior data is less than or equal to a second preset volume, determining that the target unlocking mode is an old-age mode, and setting the target unlocking mode as the normal door handle unlocking force.
7. The unlocking method based on the face recognition according to any one of claims 1 to 6, wherein after the step of obtaining the video information sent by the preset acquisition device, the method further comprises:
analyzing each video picture in the standard video information and/or the video information to be identified;
if a moving object exists in the standard video information and/or the video information to be identified, acquiring an outer edge outline of the moving object;
and if the outer edge contour is a human body contour, judging that the standard video information and/or the video information to be identified comprise a human face image.
8. The utility model provides an unlocking means based on face identification which characterized in that, unlocking means based on face identification includes:
the acquisition module is used for acquiring video information sent by the preset acquisition equipment, wherein the video information comprises video information to be identified and standard video information;
the first processing module is used for processing the standard face image to obtain the standard texture features of the standard face image when the standard video information comprises the standard face image, and updating and storing the standard texture features to a preset database;
the second processing module is used for acquiring texture features to be recognized of the face image to be recognized when the video information to be recognized comprises the face image to be recognized;
and the instruction execution module is used for comparing the texture features to be identified with each pre-stored standard texture feature in a preset database, and executing an unlocking instruction when a target standard texture feature matched with the texture features to be identified exists in the preset database.
9. The unlocking equipment based on the face recognition is characterized by comprising the following components: a memory, a processor and a face recognition based unlocking program stored on the memory and operable on the processor, wherein the face recognition based unlocking program when executed by the processor implements the steps of the face recognition based unlocking method according to any one of claims 1 to 7.
10. A computer storage medium, characterized in that the computer storage medium stores thereon a face recognition-based unlocking program, and the face recognition-based unlocking program is executed by a processor to implement the steps of the face recognition-based unlocking method according to any one of claims 1 to 7.
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