CN113640897A - Method and device for detecting human body in space, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses a method and a device for detecting human bodies in space, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor, and constructing a temperature sensing data matrix based on the plurality of temperature sensing data; the target sensor is provided with a Fresnel lens; determining a fixed matrix area and an interpolation matrix area in a temperature sensing data matrix according to the installation position of a target sensor in a target space; performing interpolation processing on the temperature sensing data matrix according to the fixed matrix area and the interpolation matrix area to determine an interpolation data matrix; and determining whether the target object exists in the target acquisition area or not according to the interpolation data matrix. By the technical scheme of the embodiment of the invention, the technical effect of accurately judging whether people exist in the space is achieved on the premise of protecting the privacy of the user.
Description
Technical Field
The embodiment of the invention relates to a temperature detection technology, in particular to a method and a device for detecting a human body in a space, electronic equipment and a storage medium.
Background
In the fields of intelligent buildings, intelligent hotels, intelligent homes and the like, whether people exist or not and areas where the people are located need to be accurately judged generally so as to carry out intelligent control and provide more comfortable environments for users.
At present, the judgment of whether a person exists and the area where the person is located are generally determined by single-point infrared sensor trigger detection or by video analysis and judgment.
However, the accuracy rate when the detection is performed by the single-point infrared sensor is low, and the use effect in the fields of intelligent buildings, intelligent hotels, intelligent homes and the like is poor. The accuracy of judging whether a person exists and the region where the person is located through the video is higher and higher, but private information of a user can be involved in the video, so that the privacy problem is easily involved, and the user experience degree is influenced. Moreover, the video acquisition needs to have enough light sources, and if the video acquisition is in a dark space, the video cannot be acquired normally and accurately, so that the problem of low judgment accuracy is caused.
Disclosure of Invention
The embodiment of the invention provides a method and a device for detecting a person in a space, electronic equipment and a storage medium, which are used for accurately judging whether the person exists in the space on the premise of protecting the privacy of a user.
In a first aspect, an embodiment of the present invention provides a method for detecting a human body in a space, where the method includes:
acquiring temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor, and constructing a temperature sensing data matrix based on the plurality of temperature sensing data; the target sensor is provided with a Fresnel lens;
determining a fixed matrix area and an interpolation matrix area in the temperature sensing data matrix according to the installation position of the target sensor in the target space;
according to the fixed matrix area and the interpolation matrix area, performing interpolation processing on the temperature sensing data matrix to determine an interpolation data matrix;
and determining whether a target object exists in the target acquisition region or not according to the interpolation data matrix.
In a second aspect, an embodiment of the present invention further provides a device for detecting a human body in a space, where the device includes:
the temperature sensing data matrix acquisition module is used for acquiring temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor and constructing a temperature sensing data matrix based on the plurality of temperature sensing data; the target sensor is provided with a Fresnel lens;
the matrix area determination module is used for determining a fixed matrix area and an interpolation matrix area in the temperature sensing data matrix according to the installation position of the target sensor in the target space;
the interpolation data matrix determining module is used for performing interpolation processing on the temperature sensing data matrix according to the fixed matrix area and the interpolation matrix area to determine an interpolation data matrix;
and the target object determining module is used for determining whether a target object exists in the target acquisition area according to the interpolation data matrix.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a method for human detection in space as in any of the embodiments of the invention.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for detecting a human body in a space according to any one of the embodiments of the present invention.
The technical scheme of the embodiment of the invention comprises the steps of acquiring the temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor, constructing a temperature sensing data matrix based on the temperature sensing data, and further, determining a fixed matrix region and an interpolation matrix region in the temperature sensing data matrix according to the installation position of the target sensor in the target space, and, according to the fixed matrix region and the interpolation matrix region, the method has the advantages that the temperature sensing data matrix is subjected to interpolation processing, the interpolation data matrix is determined, whether a target object exists in the target acquisition area or not is determined according to the interpolation data matrix, the problem that the accuracy for judging whether a person exists in the space is low and the problem that the privacy of a user is revealed when the video is judged are solved, and the technical effect that whether a person exists in the space or not is accurately judged on the premise that the privacy of the user is protected is achieved.
Drawings
In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, a brief description is given below of the drawings used in describing the embodiments. It should be clear that the described figures are only views of some of the embodiments of the invention to be described, not all, and that for a person skilled in the art, other figures can be derived from these figures without inventive effort.
Fig. 1 is a schematic flow chart of a method for detecting a human body in a space according to an embodiment of the present invention;
fig. 2 is a schematic position diagram of a target sensor and a fresnel lens according to an embodiment of the invention;
fig. 3 is a schematic flow chart of a method for detecting a human body in a space according to a second embodiment of the present invention;
FIG. 4 is a schematic view of a first installation position of a target sensor according to a second embodiment of the present invention;
fig. 5 is a schematic diagram of a fixed matrix region and an interpolation matrix region in a first temperature sensing data matrix according to a second embodiment of the present invention;
FIG. 6 is a schematic view of a second installation position of the target sensor according to the second embodiment of the present invention;
fig. 7 is a schematic diagram of a fixed matrix region and an interpolation matrix region in a second temperature sensing data matrix according to a second embodiment of the present invention;
FIG. 8 is a schematic view of a third installation position of the target sensor according to the second embodiment of the present invention;
fig. 9 is a schematic diagram of a fixed matrix region and an interpolation matrix region in a third temperature sensing data matrix according to a second embodiment of the present invention;
fig. 10 is a schematic diagram of a first data matrix obtained by inserting data rows to be interpolated and data columns to be interpolated between a fixed matrix area and an interpolation matrix area according to a second embodiment of the present invention;
fig. 11 is a schematic diagram of a second data matrix obtained by inserting data rows to be interpolated and data columns to be interpolated between a fixed matrix region and an interpolation matrix region according to the second embodiment of the present invention;
fig. 12 is a schematic diagram of a third data matrix obtained by inserting data rows to be interpolated and data columns to be interpolated between a fixed matrix region and an interpolation matrix region according to the second embodiment of the present invention;
fig. 13 is a first data matrix obtained after data lines to be interpolated and data columns to be interpolated are inserted according to a second embodiment of the present invention;
fig. 14 is a second data matrix obtained after data lines to be interpolated and data columns to be interpolated are inserted according to the second embodiment of the present invention;
fig. 15 is a third data matrix obtained after inserting data lines to be interpolated and data columns to be interpolated according to the second embodiment of the present invention;
fig. 16 is a schematic structural diagram of a device for detecting a human body in a space according to a third embodiment of the present invention;
fig. 17 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a schematic flow chart of a method for detecting a human body in a space according to an embodiment of the present invention, which is applicable to detecting whether a human body exists in a target acquisition area in a target space on the premise of protecting privacy of a user.
As shown in fig. 1, the method of this embodiment specifically includes the following steps:
s110, temperature sensing data of a plurality of target collecting points in a target collecting area in a target space collected by a target sensor are obtained, and a temperature sensing data matrix is constructed based on the plurality of temperature sensing data.
Wherein the target sensor may be a temperature sensor, for example: an 8 x 8 thermal imager sensor model AMG8833, and the like. A fresnel lens is mounted on the object sensor to expand the detection range, as shown in fig. 2. The target space may be a room to be detected. The target acquisition area may be an area that the target sensor can cover for acquisition. The target acquisition points may be respective data acquisition points in the target acquisition area. The temperature sensing data may be a temperature value of a target collection point collected by the target sensor. The temperature sensing data matrix can be a matrix formed by temperature sensing data according to the position relation of target acquisition points.
Specifically, the target sensor can detect temperature sensing data of each target acquisition point in a target acquisition area in the target space. Furthermore, the collected temperature sensing data can be arranged according to the position relation of each target collection point to construct a temperature sensing data matrix.
And S120, determining a fixed matrix area and an interpolation matrix area in the temperature sensing data matrix according to the installation position of the target sensor in the target space.
The installation position may be a position of the target sensor in the target space, and may be, for example, a ceiling or the like. The fixed matrix area may be an area in which the temperature sensing data matrix is fixed and does not need to be interpolated. The interpolation matrix area may be an area in the temperature sensing data matrix that needs to be interpolated.
Specifically, according to the installation position of the target sensor in the target space, it can be determined that a matrix region formed by temperature sensing data corresponding to a region, which is detected by the target sensor and is not affected by the fresnel lens and changed, is a fixed matrix region in the temperature sensing data matrix. The area of the temperature sensing data matrix other than the fixed matrix area may be an interpolation matrix area.
It should be noted that, when the fresnel lens is used, the detection region may be reduced nonlinearly, that is, the area of the region represented by the central pixel is smaller than the area represented by the external pixels. Therefore, to solve this problem, interpolation may be inserted into the temperature sensing data corresponding to the external pixel points to equalize the nonlinear change of the area of the region.
And S130, performing interpolation processing on the temperature sensing data matrix according to the fixed matrix area and the interpolation matrix area, and determining an interpolation data matrix.
The interpolation data matrix may be a matrix formed by the fixed matrix region and the temperature sensing data in the interpolation matrix region after interpolation processing.
Specifically, the fixed matrix area is kept unchanged, and interpolation processing is performed on the boundary of the fixed matrix area and the interpolation matrix area, so that the interpolation processing of the temperature sensing data matrix can be completed. Further, the matrix after the interpolation process may be used as the interpolation data matrix.
The interpolation processing may be various interpolation processing methods such as a nearest neighbor method, a bilinear interpolation method, a cubic interpolation method, and the like, and may be selected according to an actual application, and is not particularly limited in this embodiment.
And S140, determining whether the target object exists in the target acquisition area or not according to the interpolation data matrix.
The target object may be a person or the like having a certain difference from the ambient temperature.
Specifically, a matrix area with a large temperature difference from an adjacent position can be determined through data analysis according to the size of each data in the interpolation data matrix, and then, it can be determined that a target object exists in the target acquisition area. If no obvious difference of data sizes exists in the interpolation data matrix, it can be determined that no target object exists in the target acquisition area.
The technical scheme of the embodiment of the invention comprises the steps of acquiring the temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor, constructing a temperature sensing data matrix based on the temperature sensing data, and further, determining a fixed matrix region and an interpolation matrix region in the temperature sensing data matrix according to the installation position of the target sensor in the target space, and, according to the fixed matrix region and the interpolation matrix region, the method has the advantages that the temperature sensing data matrix is subjected to interpolation processing, the interpolation data matrix is determined, whether a target object exists in the target acquisition area or not is determined according to the interpolation data matrix, the problem that the accuracy for judging whether a person exists in the space is low and the problem that the privacy of a user is revealed when the video is judged are solved, and the technical effect that whether a person exists in the space or not is accurately judged on the premise that the privacy of the user is protected is achieved.
Example two
Fig. 3 is a schematic flow chart of a method for detecting a human body in a space according to a second embodiment of the present invention, and in this embodiment, on the basis of the foregoing embodiments, reference may be made to the technical solution of this embodiment for a determination method of a fixed matrix region and an interpolation matrix region, a difference method of a temperature sensing data matrix, and a determination method of a target object. The same or corresponding terms as those in the above embodiments are not explained in detail herein.
As shown in fig. 3, the method of this embodiment specifically includes the following steps:
s210, temperature sensing data of a plurality of target collecting points in a target collecting area in a target space collected by a target sensor are obtained, and a temperature sensing data matrix is constructed based on the plurality of temperature sensing data.
S220, determining the projection position of the installation position of the target sensor in the target space in the target acquisition region, determining a fixed matrix region based on the projection position, and determining the region except the fixed matrix region in the temperature sensing data matrix as an interpolation matrix region.
The fixed matrix area comprises temperature sensing data corresponding to the projection position. The projection position may be a position of an orthographic projection of the mounting position of the object sensor in the object acquisition region.
Specifically, the projection position in the target acquisition region may be determined according to the installation position of the target sensor in the target space. Furthermore, the area corresponding to the projection position in the temperature sensing data matrix may be set as a fixed matrix area. And, the area except the fixed matrix area in the temperature sensing data matrix may be an interpolation matrix area.
For example, fig. 4 is a schematic diagram of a first installation position of the target sensor according to the second embodiment of the present invention. Wherein the target sensor is installed in a central region directly above the target space. Furthermore, it is possible to determine a solid area as a fixed matrix area and a hollow area as an interpolation matrix area in the temperature sensing data matrix of fig. 5 according to the projection position of the installation position of the target sensor in the target acquisition area. Fig. 6 is a schematic diagram of a second installation position of the target sensor according to the second embodiment of the present invention. The target sensor is installed at the center of any side right above the target space. Further, it is possible to determine a solid area as a fixed matrix area and a hollow area as an interpolation matrix area in the temperature sensing data matrix of fig. 7 according to the projected position of the mounting position of the target sensor in the target acquisition area. Fig. 8 is a schematic diagram of a third installation position of the target sensor according to the second embodiment of the present invention. The target sensor is arranged at the position of any angle right above the target space. Further, it is possible to determine a solid area as a fixed matrix area and a hollow area as an interpolation matrix area in the temperature sensing data matrix of fig. 9 according to the projected position of the mounting position of the target sensor in the target acquisition area.
And S230, inserting data rows to be interpolated and data columns to be interpolated between the fixed matrix area and the interpolation matrix area.
The data row to be interpolated may be an empty data row inserted in the temperature sensing data matrix. The data column to be interpolated may be an empty data column inserted in the temperature sensing data matrix.
Specifically, a data row to be interpolated and a data column to be interpolated may be inserted at positions where four sides between the fixed matrix region and the interpolation matrix region are located, so as to perform subsequent interpolation processing.
For example, for the temperature sensing data matrix shown in fig. 5, a data matrix shown in fig. 10 may be obtained by inserting a data line to be interpolated and a data column to be interpolated between the fixed matrix region and the interpolation matrix region, where the regions containing oblique lines are the data line to be interpolated and the data column to be interpolated. For the temperature sensing data matrix shown in fig. 7, a data matrix shown in fig. 11 can be obtained by inserting a data line to be interpolated and a data column to be interpolated between the fixed matrix region and the interpolation matrix region, where the region containing the oblique line is the data line to be interpolated and the data column to be interpolated. For the temperature sensing data matrix shown in fig. 9, a data matrix shown in fig. 12 can be obtained by inserting a data line to be interpolated and a data column to be interpolated between the fixed matrix region and the interpolation matrix region, where the region containing the oblique line is the data line to be interpolated and the data column to be interpolated.
And S240, respectively inserting a data row to be interpolated and a data column to be interpolated between adjacent data rows and adjacent data columns in the interpolation matrix area.
Specifically, a data row to be interpolated may be inserted between every two adjacent data rows in the interpolation matrix area, and a data column to be interpolated may be inserted between every two adjacent data columns in the interpolation matrix area.
Illustratively, on the basis of the data matrix shown in fig. 10, after the data row to be interpolated and the data column to be interpolated are respectively inserted between the adjacent data row and the adjacent data column in the interpolation matrix region, the data matrix shown in fig. 13 can be obtained. On the basis of the data matrix shown in fig. 11, after the data row to be interpolated and the data column to be interpolated are respectively inserted between the adjacent data row and the adjacent data column in the interpolation matrix region, the data matrix shown in fig. 14 can be obtained. On the basis of the data matrix shown in fig. 12, after the data row to be interpolated and the data column to be interpolated are respectively inserted between the adjacent data row and the adjacent data column in the interpolation matrix region, the data matrix shown in fig. 15 can be obtained. In fig. 13, fig. 14 and fig. 15, the regions containing oblique lines are the data lines to be interpolated and the data columns to be interpolated.
And S250, determining interpolation data in each data line to be interpolated and each data column to be interpolated according to the temperature sensing data in the temperature sensing data matrix.
Specifically, the interpolation data may be data values in a data line to be interpolated and a data column to be interpolated, which are determined according to an interpolation processing method.
Alternatively, the interpolated data may be determined by:
step one, two reference sensing data adjacent to each data point to be interpolated in the data line to be interpolated and the data column to be interpolated are determined from the temperature sensing data of the temperature sensing data matrix.
The data point to be interpolated may be each data point in the data line to be interpolated and the data column to be interpolated. The reference sensing data may be temperature sensing data adjacent to the data point to be interpolated, for example: the reference sensing data corresponding to the data point to be interpolated in the data line to be interpolated can be temperature sensing data adjacent to the data point to be interpolated in the upper line and the lower line of the data point to be interpolated; the reference sensing data corresponding to the data point to be interpolated in the data column to be interpolated may be temperature sensing data located in the left column and the right column of the data point to be interpolated and adjacent to the data point to be interpolated.
Specifically, for each data point to be interpolated in the data line to be interpolated and the data column to be interpolated, two reference sensing data corresponding to the data point to be interpolated may be determined for subsequent interpolation calculation.
And step two, aiming at each data point to be interpolated, determining interpolation data according to the average value of two reference sensing data adjacent to the data point to be interpolated.
Specifically, for each data point to be interpolated, an average value of two reference sensing data corresponding to the data point to be interpolated may be calculated, and the average value may be used as the interpolation data of the data point to be interpolated. Further, interpolation data corresponding to all data points to be interpolated can be determined.
For example, for each data point to be interpolated in the data line to be interpolated, two temperature sensing data adjacent to the data point to be interpolated in the previous line and the next line of the line where the data point to be interpolated is determined as reference sensing data. If the two temperature sensing data adjacent to the data point to be interpolated are other data points to be interpolated, the reference sensing data does not need to be determined. And determining interpolation data of the data point to be interpolated in the data line to be interpolated according to the average value of the two adjacent reference sensing data. And then, for each data point to be interpolated in the data array to be interpolated, determining two temperature sensing data adjacent to the data point to be interpolated in the left array and the right array of the array where the data point to be interpolated is as reference sensing data. If the data point to be interpolated of the reference sensing data cannot be determined in the previous step, the interpolated data on the left and right sides adjacent to the data point to be interpolated can be used as the reference sensing data. And determining interpolation data of the data point to be interpolated in the data column to be interpolated according to the average value of the two adjacent reference sensing data.
It should be noted that, in the above example, the interpolation data of each data point to be interpolated in the data line to be interpolated is determined first, and then the interpolation data of each data point to be interpolated in the data column to be interpolated is determined, in an actual application process, the interpolation data of each data point to be interpolated in the data line to be interpolated may also be determined first, and then the interpolation data of each data point to be interpolated in the data line to be interpolated is determined, which is not specifically limited in this embodiment.
And S260, determining an interpolation data matrix according to the temperature sensing data and the interpolation data.
Specifically, the interpolation data is filled in the corresponding data point to be interpolated, and a data matrix formed by the temperature sensing data and the interpolation data is used as an interpolation data matrix.
And S270, determining whether a target object exists in the target acquisition area or not according to the interpolation data matrix.
Specifically, if a matrix area with a large temperature difference with an adjacent position exists, it is determined that a target object exists in the target acquisition area. If no obvious difference of data sizes exists in the interpolation data matrix, it can be determined that no target object exists in the target acquisition area.
Optionally, whether the target object exists in the target acquisition area may be accurately determined according to the following steps:
step one, according to the interpolation data matrix, determining the temperature minimum value and the temperature average value in the interpolation data matrix
Specifically, the minimum value of the interpolation data matrix may be determined as the lowest temperature value according to the corresponding numerical value of each data point in the interpolation data matrix. And, the average value of the values corresponding to the respective data points may be calculated and taken as the temperature average value.
And step two, determining a first reference value and a second reference value corresponding to each temperature data value in the interpolation data matrix according to the interpolation data matrix, the temperature minimum value and the temperature average value.
The first reference value is the difference between the temperature data value and the lowest temperature value, and the second reference value is the difference between the temperature data value and the average temperature value.
Specifically, for the temperature data value corresponding to each data point in the interpolation data matrix, the difference between the temperature data value and the lowest temperature value may be calculated as the first reference value corresponding to the temperature data value, and the difference between the temperature data value and the average temperature value may be calculated as the second reference value corresponding to the temperature data value.
And step three, determining at least one reference matrix corresponding to the interpolation data matrix according to the size of the preset reference matrix.
Here, the preset reference matrix size may be a preset matrix size, for example, 2 × 2 or the like.
Specifically, each data matrix with the size of the preset reference matrix in the interpolated data matrix may be used as a reference matrix, and further, all reference matrices corresponding to the interpolated data matrix may be determined.
And fourthly, summing the first reference value and the second reference value corresponding to each temperature data value in the reference matrix aiming at each reference matrix to obtain the temperature value to be detected.
The temperature value to be detected may be a data value obtained by summing a first reference value and a second reference value corresponding to each temperature data value in the reference matrix.
In particular, for each reference matrix, for each temperature data value in the reference matrix a first reference value and a second reference value corresponding thereto may be determined. And then, summing the first reference values and the second reference values to obtain a sum value which is a temperature value to be detected.
For example, if the size of the reference matrix is 2 × 2, it may be determined that the number of temperature data values in the reference matrix is 4. Furthermore, the first reference value and the second reference value corresponding to each of the 4 temperature data values may be determined, that is, the 4 first reference values and the 4 second reference values may be determined. And summing the 8 data values of the 4 first reference values and the 4 second reference values, and taking the obtained sum value as a temperature value to be detected.
And step five, if at least one temperature value to be detected is larger than a preset temperature threshold value, determining that a target object exists in the target acquisition area.
The preset temperature threshold may be a preset value, and is used to measure whether a target object exists in the target collection area.
Specifically, the temperature value to be detected is compared with a preset temperature threshold, and if at least one temperature value to be detected is larger than the preset temperature threshold, it can be determined that the target object exists in the target acquisition area. If each temperature value to be detected is smaller than or equal to the preset temperature threshold value, it can be determined that no target object exists in the target acquisition area.
For example, the preset temperature threshold may be set to 10 degrees celsius, and if a certain temperature value to be detected is greater than 10 degrees celsius, it may be determined that a target object exists in the target acquisition area. If each temperature value to be detected is less than or equal to 10 ℃, it can be determined that no target object exists in the target acquisition area.
Optionally, the speed of determining whether the target object exists may be increased by determining a highest temperature value in the interpolated data matrix, and specifically, the method may include the following steps:
step one, determining a temperature maximum value, a temperature minimum value and a temperature average value in an interpolation data matrix according to the interpolation data matrix.
Specifically, according to the numerical values corresponding to the data points in the interpolation data matrix, the minimum value is determined to be the lowest temperature value, and the maximum value is determined to be the highest temperature value. And, the average value of the values corresponding to the respective data points may be calculated and taken as the temperature average value.
And step two, determining a first reference value and a second reference value corresponding to each temperature data value in the interpolation data matrix according to the interpolation data matrix, the temperature minimum value and the temperature average value.
And step three, determining at least one reference matrix containing the highest temperature value in the interpolation data matrix according to the size of the preset reference matrix.
Specifically, each data matrix with the preset reference matrix size in the interpolated data matrix may be used as a reference matrix, and then, the reference matrix containing the highest temperature value may be determined as a reference matrix to be used subsequently.
And fourthly, summing the first reference value and the second reference value corresponding to each temperature data value in the reference matrix aiming at each reference matrix to obtain the temperature value to be detected.
And step five, if at least one temperature value to be detected is larger than a preset temperature threshold value, determining that a target object exists in the target acquisition area.
It should be noted that, since the temperature value to be detected is the sum of the first reference value and the second reference value corresponding to each temperature data value in the reference matrix, the temperature value to be detected including the reference matrix corresponding to the highest temperature value can be roughly calculated. In general, the value of the temperature to be detected, which includes the reference matrix corresponding to the highest value of the temperature, is relatively high.
It should be further noted that, in order to improve the accuracy of detecting whether a target object exists in the target acquisition area, under the condition that the to-be-detected temperature values of the reference matrix including the highest temperature value are not greater than the preset temperature threshold value, the to-be-detected temperature values corresponding to other reference matrices may be calculated, compared, and determined.
On the basis of the foregoing embodiments, if a target object exists in the target acquisition area, the activity area of the target object may be further determined, which specifically may be:
for each reference matrix, if the temperature value to be detected of the reference matrix is greater than a preset temperature threshold value, determining that the reference matrix and the reference matrix are active matrices; and determining the activity area of the target object according to each activity matrix.
The activity matrix may be a reference matrix in which the temperature value to be detected is greater than a preset temperature threshold. The active area may be an area of the target acquisition area corresponding to the active matrix.
Specifically, if the to-be-detected temperature value of the reference matrix is greater than the preset temperature threshold, it may be determined that the reference matrix is an active matrix, that is, it may be determined that there is an obvious difference between the temperature in the active matrix and the temperature in the entire interpolation data matrix. Furthermore, the area corresponding to the active matrix in the target acquisition area can be determined according to the corresponding relation between the active matrix and each area in the target acquisition area.
It should be noted that, a corresponding relationship between the interpolated data matrix and each region point in the target acquisition region may be established, so as to determine a region corresponding to each data point in the interpolated data matrix.
The technical scheme of the embodiment of the invention comprises the steps of acquiring temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor, constructing a temperature sensing data matrix based on the temperature sensing data, further determining the projection position of the installation position of the target sensor in the target acquisition area, determining a fixed matrix area based on the projection position, determining an area except the fixed matrix area in the temperature sensing data matrix as an interpolation matrix area, inserting a data row to be interpolated and a data column to be interpolated between the fixed matrix area and the interpolation matrix area, respectively inserting the data row to be interpolated and the data column to be interpolated between adjacent data rows in the interpolation matrix area, and determining interpolation data in each data row to be interpolated and each data column to be interpolated according to the temperature sensing data in the temperature sensing data matrix, the interpolation data matrix is determined according to the temperature sensing data and the interpolation data, whether a target object exists in the target acquisition area is determined according to the interpolation data matrix, the problem that the accuracy for judging whether a person exists in the space is low is solved, the problem that the privacy of the user is revealed when the video is judged is solved, and the technical effect of accurately judging whether the person exists in the space on the premise of protecting the privacy of the user is achieved.
EXAMPLE III
Fig. 16 is a schematic structural diagram of a device for detecting a human body in a space according to a third embodiment of the present invention, where the device includes: a temperature sensing data matrix acquisition module 410, a matrix region determination module 420, an interpolated data matrix determination module 430, and a target object determination module 440.
The temperature sensing data matrix acquisition module 410 is configured to acquire temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor, and construct a temperature sensing data matrix based on the plurality of temperature sensing data; the target sensor is provided with a Fresnel lens; a matrix area determination module 420, configured to determine a fixed matrix area and an interpolation matrix area in the temperature sensing data matrix according to an installation position of the target sensor in the target space; an interpolation data matrix determining module 430, configured to perform interpolation processing on the temperature sensing data matrix according to the fixed matrix region and the interpolation matrix region, and determine an interpolation data matrix; and a target object determining module 440, configured to determine whether a target object exists in the target acquisition area according to the interpolated data matrix.
Optionally, the matrix area determining module 420 is further configured to determine a projection position of the installation position of the target sensor in the target space in the target acquisition area, determine a fixed matrix area based on the projection position, and determine an area of the temperature sensing data matrix excluding the fixed matrix area as an interpolation matrix area; wherein the fixed matrix region includes temperature sensing data corresponding to the projection location.
Optionally, the interpolation data matrix determining module 430 is further configured to insert a data row to be interpolated and a data column to be interpolated between the fixed matrix region and the interpolation matrix region; respectively inserting a data row to be interpolated and a data column to be interpolated between adjacent data rows and adjacent data columns in the interpolation matrix area; determining interpolation data in each data line to be interpolated and each data column to be interpolated according to the temperature sensing data in the temperature sensing data matrix; and determining an interpolation data matrix according to the temperature sensing data and the interpolation data.
Optionally, the interpolation data matrix determining module 430 is further configured to determine, from the temperature sensing data of the temperature sensing data matrix, two reference sensing data adjacent to each data point to be interpolated in the data line to be interpolated and the data column to be interpolated; and determining interpolation data according to the average value of two reference sensing data adjacent to each data point to be interpolated.
Optionally, the target object determining module 440 is further configured to determine a temperature lowest value and a temperature average value in the interpolated data matrix according to the interpolated data matrix; determining a first reference value and a second reference value corresponding to each temperature data value in the interpolation data matrix according to the interpolation data matrix, the temperature minimum value and the temperature average value; wherein the first reference value is a difference between the temperature data value and the temperature lowest value, and the second reference value is a difference between the temperature data value and the temperature average value; determining at least one reference matrix corresponding to the interpolation data matrix according to the size of a preset reference matrix; for each reference matrix, summing a first reference value and a second reference value corresponding to each temperature data value in the reference matrix to obtain a temperature value to be detected; and if at least one temperature value to be detected is larger than a preset temperature threshold value, determining that the target object exists in the target acquisition area.
Optionally, the apparatus further comprises: the active area determining module is used for determining that the reference matrix is an active matrix if the temperature value to be detected of the reference matrix is greater than the preset temperature threshold value for each reference matrix; and determining the activity area of the target object according to each activity matrix.
Optionally, the target object determining module 440 is further configured to determine a temperature maximum value, a temperature minimum value, and a temperature average value in the interpolated data matrix according to the interpolated data matrix; determining a first reference value and a second reference value corresponding to each temperature data value in the interpolation data matrix according to the interpolation data matrix, the temperature minimum value and the temperature average value; wherein the first reference value is a difference between the temperature data value and the temperature lowest value, and the second reference value is a difference between the temperature data value and the temperature average value; determining at least one reference matrix containing the highest temperature value in the interpolation data matrix according to the size of a preset reference matrix; for each reference matrix, summing a first reference value and a second reference value corresponding to each temperature data value in the reference matrix to obtain a temperature value to be detected; and if at least one temperature value to be detected is larger than a preset temperature threshold value, determining that the target object exists in the target acquisition area.
The technical scheme of the embodiment of the invention comprises the steps of acquiring the temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor, constructing a temperature sensing data matrix based on the temperature sensing data, and further, determining a fixed matrix region and an interpolation matrix region in the temperature sensing data matrix according to the installation position of the target sensor in the target space, and, according to the fixed matrix region and the interpolation matrix region, the method has the advantages that the temperature sensing data matrix is subjected to interpolation processing, the interpolation data matrix is determined, whether a target object exists in the target acquisition area or not is determined according to the interpolation data matrix, the problem that the accuracy for judging whether a person exists in the space is low and the problem that the privacy of a user is revealed when the video is judged are solved, and the technical effect that whether a person exists in the space or not is accurately judged on the premise that the privacy of the user is protected is achieved.
The device for detecting the human body in the space provided by the embodiment of the invention can execute the method for detecting the human body in the space provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
It should be noted that, the units and modules included in the apparatus are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the embodiment of the invention.
Example four
Fig. 17 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention. FIG. 17 illustrates a block diagram of an exemplary electronic device 40 suitable for use in implementing embodiments of the present invention. The electronic device 40 shown in fig. 17 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention.
As shown in fig. 17, the electronic device 40 is in the form of a general purpose computing device. The components of electronic device 40 may include, but are not limited to: one or more processors or processing units 401, a system memory 402, and a bus 403 that couples the various system components (including the system memory 402 and the processing unit 401).
The system memory 402 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)404 and/or cache memory 405. The electronic device 40 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 406 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 17, commonly referred to as a "hard drive"). Although not shown in FIG. 17, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 403 by one or more data media interfaces. System memory 402 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 408 having a set (at least one) of program modules 407 may be stored, for example, in system memory 402, such program modules 407 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 407 generally perform the functions and/or methods of the described embodiments of the invention.
The electronic device 40 may also communicate with one or more external devices 409 (e.g., keyboard, pointing device, display 410, etc.), with one or more devices that enable a user to interact with the electronic device 40, and/or with any devices (e.g., network card, modem, etc.) that enable the electronic device 40 to communicate with one or more other computing devices. Such communication may be through input/output (I/O) interface 411. Also, the electronic device 40 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 412. As shown, the network adapter 412 communicates with the other modules of the electronic device 40 over the bus 403. It should be appreciated that although not shown in FIG. 17, other hardware and/or software modules may be used in conjunction with electronic device 40, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 401 executes various functional applications and data processing by running programs stored in the system memory 402, for example, implementing a human body detection method in space provided by an embodiment of the present invention.
EXAMPLE five
An embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor, perform a method for detecting a human body in a space, the method including:
acquiring temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor, and constructing a temperature sensing data matrix based on the plurality of temperature sensing data; the target sensor is provided with a Fresnel lens;
determining a fixed matrix area and an interpolation matrix area in the temperature sensing data matrix according to the installation position of the target sensor in the target space;
according to the fixed matrix area and the interpolation matrix area, performing interpolation processing on the temperature sensing data matrix to determine an interpolation data matrix;
and determining whether a target object exists in the target acquisition region or not according to the interpolation data matrix.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for embodiments of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method of detecting a person in space, comprising:
acquiring temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor, and constructing a temperature sensing data matrix based on the plurality of temperature sensing data; the target sensor is provided with a Fresnel lens;
determining a fixed matrix area and an interpolation matrix area in the temperature sensing data matrix according to the installation position of the target sensor in the target space;
according to the fixed matrix area and the interpolation matrix area, performing interpolation processing on the temperature sensing data matrix to determine an interpolation data matrix;
and determining whether a target object exists in the target acquisition region or not according to the interpolation data matrix.
2. The method of claim 1, wherein determining a fixed matrix region and an interpolated matrix region in the temperature sensing data matrix based on the installation location of the target sensor in the target space comprises:
determining the projection position of the installation position of the target sensor in the target space in the target acquisition region, determining a fixed matrix region based on the projection position, and determining a region except the fixed matrix region in the temperature sensing data matrix as an interpolation matrix region; wherein the fixed matrix region includes temperature sensing data corresponding to the projection location.
3. The method of claim 1, wherein interpolating the temperature sensing data matrix from the fixed matrix region and the interpolated matrix region to determine an interpolated data matrix comprises:
inserting data rows to be interpolated and data columns to be interpolated between the fixed matrix area and the interpolation matrix area;
respectively inserting a data row to be interpolated and a data column to be interpolated between adjacent data rows and adjacent data columns in the interpolation matrix area;
determining interpolation data in each data line to be interpolated and each data column to be interpolated according to the temperature sensing data in the temperature sensing data matrix;
and determining an interpolation data matrix according to the temperature sensing data and the interpolation data.
4. The method of claim 3, wherein determining interpolation data in each row and column of data to be interpolated from temperature sensing data in the matrix of temperature sensing data comprises:
determining two reference sensing data adjacent to each data point to be interpolated in the data line to be interpolated and the data column to be interpolated from the temperature sensing data of the temperature sensing data matrix;
and determining interpolation data according to the average value of two reference sensing data adjacent to each data point to be interpolated.
5. The method of claim 1, wherein said determining whether a target object is present in the target acquisition region according to the interpolated data matrix comprises:
according to the interpolation data matrix, determining a temperature minimum value and a temperature average value in the interpolation data matrix;
determining a first reference value and a second reference value corresponding to each temperature data value in the interpolation data matrix according to the interpolation data matrix, the temperature minimum value and the temperature average value; wherein the first reference value is a difference between the temperature data value and the temperature lowest value, and the second reference value is a difference between the temperature data value and the temperature average value;
determining at least one reference matrix corresponding to the interpolation data matrix according to the size of a preset reference matrix;
for each reference matrix, summing a first reference value and a second reference value corresponding to each temperature data value in the reference matrix to obtain a temperature value to be detected;
and if at least one temperature value to be detected is larger than a preset temperature threshold value, determining that the target object exists in the target acquisition area.
6. The method of claim 5, further comprising:
for each reference matrix, if the temperature value to be detected of the reference matrix is greater than the preset temperature threshold value, determining that the reference matrix and the reference matrix are active matrices;
and determining the activity area of the target object according to each activity matrix.
7. The method of claim 1, wherein said determining whether a target object is present in the target acquisition region according to the interpolated data matrix comprises:
determining a temperature maximum value, a temperature minimum value and a temperature average value in the interpolation data matrix according to the interpolation data matrix;
determining a first reference value and a second reference value corresponding to each temperature data value in the interpolation data matrix according to the interpolation data matrix, the temperature minimum value and the temperature average value; wherein the first reference value is a difference between the temperature data value and the temperature lowest value, and the second reference value is a difference between the temperature data value and the temperature average value;
determining at least one reference matrix containing the highest temperature value in the interpolation data matrix according to the size of a preset reference matrix;
for each reference matrix, summing a first reference value and a second reference value corresponding to each temperature data value in the reference matrix to obtain a temperature value to be detected;
and if at least one temperature value to be detected is larger than a preset temperature threshold value, determining that the target object exists in the target acquisition area.
8. An in-space human detection apparatus, comprising:
the temperature sensing data matrix acquisition module is used for acquiring temperature sensing data of a plurality of target acquisition points in a target acquisition area in a target space acquired by a target sensor and constructing a temperature sensing data matrix based on the plurality of temperature sensing data; the target sensor is provided with a Fresnel lens;
the matrix area determination module is used for determining a fixed matrix area and an interpolation matrix area in the temperature sensing data matrix according to the installation position of the target sensor in the target space;
the interpolation data matrix determining module is used for performing interpolation processing on the temperature sensing data matrix according to the fixed matrix area and the interpolation matrix area to determine an interpolation data matrix;
and the target object determining module is used for determining whether a target object exists in the target acquisition area according to the interpolation data matrix.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a method for in-space human detection as recited in any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the method of human detection in space of any one of claims 1 to 7.
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