CN110879975B - Personnel flow detection method and device and electronic equipment - Google Patents
Personnel flow detection method and device and electronic equipment Download PDFInfo
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Abstract
The embodiment of the disclosure provides a personnel flow detection method, a personnel flow detection device and electronic equipment, belonging to the technical field of image processing, wherein the method comprises the following steps: acquiring multiple frames of images corresponding to a preset area, wherein the preset area comprises a target area; extracting a key region image of the target pedestrian from the preset region image containing the target pedestrian in each frame; determining coordinates of an image area corresponding to the key part of the target pedestrian in the reference plane coordinate system; judging whether the coordinates of the image area corresponding to the key part of the target pedestrian exceed the coordinate set of the image area corresponding to the target area, and judging whether the duration of the key part of the target pedestrian in the target area is matched with a preset threshold value; and if the pedestrian flow rate is consistent with the target pedestrian flow rate, determining that the target pedestrian passes through a target area, and updating the pedestrian flow rate of the target area. Therefore, the accuracy of personnel flow detection is improved.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to a method and an apparatus for detecting a flow of people, and an electronic device.
Background
At present, the mode of monitoring the staff flow in a market or a scenic spot by using an image acquisition device is increasingly popularized, but the existing staff flow detection scheme cannot screen the staff repeatedly entering a monitoring scene, so that the accuracy of staff flow detection is poor.
Therefore, the existing personnel flow detection method has the problem of poor flow detection accuracy.
Disclosure of Invention
In view of this, the embodiments of the present disclosure provide a people flow rate detection method, which at least partially solves the problems in the prior art.
In a first aspect, an embodiment of the present disclosure provides a method for detecting a flow of people, where the method includes:
acquiring multiple frames of images corresponding to a preset area, wherein the preset area comprises a target area;
extracting a key region image of the target pedestrian from the preset region image containing the target pedestrian in each frame;
determining the coordinates of the image area corresponding to the key part of the target pedestrian in a reference plane coordinate system by taking a plane coordinate system corresponding to the preset area image as the reference plane coordinate system;
judging whether the coordinates of the image area corresponding to the key part of the target pedestrian exceed the coordinate set of the image area corresponding to the target area, and judging whether the duration of the key part of the target pedestrian in the target area is matched with a preset threshold value;
if the coordinates corresponding to the key part image of the target pedestrian exceed the coordinate set corresponding to the image of the target area and the time of the key part of the target pedestrian in the image of the target area is matched with a preset threshold value, determining that the target pedestrian passes through the target area, and updating the personnel flow of the target area;
if the coordinate corresponding to the key part image of the target pedestrian does not exceed the coordinate set corresponding to the image of the target area or the time that the key part of the target pedestrian is located in the image of the target area is not matched with a preset threshold value, determining that the target pedestrian does not cross the target area, and forbidding updating of the personnel flow of the target area.
According to a specific implementation manner of the embodiment of the present disclosure, before the step of determining whether the coordinate corresponding to the key portion image of the target pedestrian exceeds the coordinate set corresponding to the target area image, the method further includes:
calculating to obtain an optimal face image according to the fact that each frame comprises the key position image of the target pedestrian;
judging whether the optimal face image is matched with a preset face library, wherein the preset face library is an optimal face image set corresponding to all pedestrians which are determined to pass through the target area in the prior personnel flow detection operation;
if the optimal face image is matched with a preset face library, forbidding the coordinate calculation of the target pedestrian;
and if the optimal face image is not matched with a preset face library, calculating the coordinates of the target pedestrian.
According to a specific implementation manner of the embodiment of the present disclosure, the face library is a face library formed in a current detection period, and the face library is emptied after each detection period is finished.
According to a specific implementation manner of the embodiment of the disclosure, the reference plane coordinate system is a plane coordinate system established by using a target pixel point of the preset area image as an origin, each basic coordinate point in the reference plane coordinate system corresponds to each pixel point of the preset area image, and the target pixel point is any pixel point of the preset area image.
According to a specific implementation manner of the embodiment of the present disclosure, the step of determining the coordinates corresponding to the key position image of the target pedestrian in each frame of image of the preset area includes:
and comparing the previously extracted key part bitmap pixel points of each frame of the target pedestrian with the original point to obtain the plane coordinates of the key part bitmap image of each frame of the target pedestrian.
According to a specific implementation of the embodiment of the present disclosure, the target pedestrian key area image includes a hand image, a leg image, and a face image.
According to a specific implementation manner of the embodiment of the present disclosure, before the step of determining whether a duration of the key part of the target pedestrian in the target area is matched with a preset threshold, the method further includes:
calculating the time of a preset sample person passing through the target area;
and calculating the average crossing time as the preset threshold according to the time of all the sample personnel passing through the target area.
In a second aspect, an embodiment of the present disclosure provides a people flow rate detection apparatus, including:
the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring multiple frames of images corresponding to a preset area, and the preset area comprises a target area;
the extraction module is used for extracting a key part image of the target pedestrian from the preset region image containing the target pedestrian in each frame;
the determining module is used for determining the coordinates of the image area corresponding to the key part of the target pedestrian in a reference plane coordinate system by taking the plane coordinate system corresponding to the preset area image as the reference plane coordinate system;
and the judging module is used for judging whether the coordinates of the image area corresponding to the key part of the target pedestrian exceed the coordinate set of the image area corresponding to the target area or not and judging whether the duration of the key part of the target pedestrian in the target area is matched with a preset threshold or not.
And if the coordinates corresponding to the key part image of the target pedestrian exceed the coordinate set corresponding to the target area image and the time of the key part of the target pedestrian in the target area image is matched with a preset threshold value, determining that the target pedestrian passes through the target area, and updating the personnel flow of the target area.
If the coordinate corresponding to the key position image of the target pedestrian does not exceed the coordinate set corresponding to the image of the target area or the time that the key position of the target pedestrian is located in the image of the target area is not matched with a preset threshold value, determining that the target pedestrian does not cross the target area, and forbidding updating the flow of the people in the target area.
In a third aspect, an embodiment of the present disclosure further provides an electronic device, where the electronic device includes:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to perform the method for detecting human traffic in any of the implementations of the first aspect or the first aspect.
In a fourth aspect, the disclosed embodiments also provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method for detecting human traffic in the first aspect or any implementation manner of the first aspect.
In a fifth aspect, the present disclosure also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, where the computer program includes program instructions, and when the program instructions are executed by a computer, the computer is caused to execute the human traffic detection method in the foregoing first aspect or any implementation manner of the first aspect.
The personnel flow detection scheme in the embodiment of the disclosure comprises the steps of collecting multiple frames of images corresponding to a preset area, wherein the preset area comprises a target area; extracting a key region image of the target pedestrian from the preset region image containing the target pedestrian in each frame; determining the coordinates of the image area corresponding to the key part of the target pedestrian in a reference plane coordinate system by taking a plane coordinate system corresponding to the preset area image as the reference plane coordinate system; judging whether the coordinates of the image area corresponding to the key part of the target pedestrian exceed the coordinate set of the image area corresponding to the target area, and judging whether the time length of the key part of the target pedestrian in the target area is matched with a preset threshold value; and if the coordinates corresponding to the key part image of the target pedestrian exceed the coordinate set corresponding to the target area image and the time of the key part of the target pedestrian in the target area image is matched with a preset threshold value, determining that the target pedestrian passes through the target area, and updating the personnel flow of the target area. If the coordinate corresponding to the key part image of the target pedestrian does not exceed the coordinate set corresponding to the image of the target area or the time that the key part of the target pedestrian is located in the image of the target area is not matched with a preset threshold value, determining that the target pedestrian does not cross the target area, and forbidding updating of the personnel flow of the target area. Through the scheme disclosed by the invention, the accuracy of personnel flow detection is improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required to be used in the embodiments will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for detecting a flow of people according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a passenger flow rate detection device according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of an electronic device provided in an embodiment of the disclosure.
Detailed Description
The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.
The embodiments of the present disclosure are described below with specific examples, and other advantages and effects of the present disclosure will be readily apparent to those skilled in the art from the disclosure in the specification. It is to be understood that the described embodiments are merely illustrative of some, and not restrictive, of the embodiments of the disclosure. The disclosure may be embodied or carried out in various other specific embodiments, and various modifications and changes may be made in the details within the description without departing from the spirit of the disclosure. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It is noted that various aspects of the embodiments are described below within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the disclosure, one skilled in the art should appreciate that one aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. In addition, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to or other than one or more of the aspects set forth herein.
It should be further noted that the drawings provided in the following embodiments are only schematic illustrations of the basic concepts of the present disclosure, and the drawings only show the components related to the present disclosure rather than the numbers, shapes and dimensions of the components in actual implementation, and the types, the numbers and the proportions of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects may be practiced without these specific details.
The embodiment of the disclosure provides a personnel flow detection method. The method for detecting the flow of people provided by the embodiment can be executed by a computing device, the computing device can be implemented as software, or implemented as a combination of software and hardware, and the computing device can be integrally arranged in a server, a terminal device and the like.
Referring to fig. 1, a method for detecting a flow of people provided in an embodiment of the present disclosure includes:
s101, collecting multiple frames of images corresponding to a preset area, wherein the preset area comprises a target area.
The personnel flow detection method provided by the embodiment of the disclosure can be applied to the personnel flow detection process in shopping malls and scenic spots.
The electronic device can be internally provided with an image acquisition module or externally connected with an image acquisition device and used for acquiring images in a preset area to be detected, wherein the preset area comprises a target area. After the image acquisition module or the image acquisition equipment acquires more than 2 frames of images in the preset area, the images can be directly sent to the processor for subsequent analysis and processing operations, the acquired images of the preset area can also be stored in a preset storage space, and when the specific time of the preset area needs to be analyzed, the corresponding images can be acquired from the preset storage space for analysis and processing.
For example, if the area where the flow of the person to be detected is set as a mall, the preset area for collecting the image may be a range from the entrance of the mall to the exit of the mall, wherein the target area is inside the mall, and the image collecting device collects at least 2 frames of images corresponding to the preset area.
And S102, extracting a key part image of the target pedestrian from the preset region image containing the target pedestrian in each frame.
Screening all images corresponding to target pedestrians from multiple frames of images corresponding to preset regions, carrying out analysis and detection processes by utilizing the preset region images of each frame containing the target pedestrians according to the screened images, and extracting the key part images of the target pedestrians from the images.
The extracted key region image of the target pedestrian may include at least one of key regions such as a hand image, a leg image, and a face image, and the key region image may further include key regions such as a shoulder image and a back image.
And S103, determining the coordinates of the image area corresponding to the key part of the target pedestrian in the reference plane coordinate system by taking the plane coordinate system corresponding to the preset area image as the reference plane coordinate system.
Optionally, a plane coordinate system is established by using the preset area image, the plane coordinate system is defined as a reference coordinate system, the reference plane coordinate system is established by using a target pixel point of the preset area image as an origin, each basic coordinate point in the reference plane coordinate system corresponds to each pixel point of the preset area image, and the target pixel point is any pixel point of the preset area image.
And comparing the previously extracted key part bitmap pixel points of each frame of the target pedestrian with the original point to obtain the plane coordinates of the key part bitmap image of each frame of the target pedestrian.
S104, judging whether the coordinates of the image area corresponding to the key part of the target pedestrian exceed the coordinate set of the image area corresponding to the target area, and judging whether the duration of the key part of the target pedestrian in the target area is matched with a preset threshold value.
For example, considering that in the daily detection process, the pedestrian may pass through the detection area by accident and thus cannot be detected, it is necessary to determine whether the requirement of the human flow detection is met by combining the moving track of the target pedestrian in the target area and the time length of the target area.
And when the target pedestrian enters the target area, timing is started, the coordinates are calculated according to each acquired frame including the key part image of the target pedestrian, and when the coordinates corresponding to the key part image including the target pedestrian exceed the target area, the timing is ended. And calculating the time length of the target pedestrian in the implementation target area, and comparing the time length with a preset threshold value so as to determine the next operation flow. Optionally, the preset threshold may be obtained by calculating the time for a preset sample person to pass through the target area, and calculating an average crossing time according to the time for all sample persons to pass through the target area, which is used as the preset threshold.
And if the coordinates of the image area corresponding to the key part of the target pedestrian exceed the coordinate set of the image area corresponding to the target area and the time length of the key part of the target pedestrian in the target area is matched with a preset threshold, executing a step S105, determining that the target pedestrian passes through the target area, and updating the personnel flow of the target area.
And if the coordinates of the image area corresponding to the key part of the target pedestrian do not exceed the coordinate set of the image area corresponding to the target area or the time length of the key part of the target pedestrian in the target area is not matched with a preset threshold, executing step S106, determining that the target pedestrian does not pass through the target area, and forbidding updating of the personnel flow of the target area.
If the electronic equipment determines that the coordinates of the image area corresponding to the key part of the target pedestrian exceeds the coordinate set of the image area corresponding to the target area and the time length of the key part of the target pedestrian in the target area is matched with a preset threshold value, determining that the target pedestrian passes through the target area, and updating the personnel flow of the target area. For example, in the case where it is confirmed that the target pedestrian has passed through the target area, it is determined that the pedestrian volume is increased by one.
If the electronic equipment judges that the coordinates of the image area corresponding to the key part of the target pedestrian do not exceed the coordinate set of the image area corresponding to the target area or the time length of the key part of the target pedestrian in the target area is not matched with a preset threshold, the electronic equipment indicates that the target pedestrian does not pass through the target area, and the personnel flow of the target area does not need to be updated.
The staff flow detection method provided by the embodiment of the disclosure is directed at real-time detection of the staff flow in the specific area, and the staff flow is judged by calculating the movement track of the target staff and the time length of the staff in the specific area. According to the method provided by the embodiment, the personnel detection precision is improved through the key position images of the target personnel, and the personnel repeatedly entering the specific area are removed in a face bank screening mode, so that the occurrence frequency of the same personnel can be avoided being repeatedly calculated, and the personnel flow detection accuracy is improved.
On the basis of the foregoing embodiment of the present disclosure, in the step S104, it is determined whether the coordinates of the image area corresponding to the target pedestrian key part exceed the coordinate set of the image area corresponding to the target area, before the method may further include:
calculating to obtain an optimal face image according to the fact that each frame comprises the key position image of the target pedestrian;
judging whether the optimal face image is matched with a preset face library, wherein the preset face library is an optimal face image set corresponding to all pedestrians which are determined to pass through the target area in the prior personnel flow detection operation;
if the optimal face image is matched with a preset face library, forbidding the coordinate calculation of the target pedestrian;
and if the optimal face image is not matched with a preset face library, calculating the coordinates of the target pedestrian.
Optionally, the face library is a face library formed in the current detection period, and the face library is emptied after each detection period is finished.
In specific implementation, the optimal face image is obtained by analyzing and calculating the acquired face image in each frame including the key part of the target pedestrian. And comparing the optimal face with a face library, and if the optimal face is matched with the face library, determining that the target person repeatedly enters the target area in the current detection period without performing coordinate calculation.
Corresponding to the above method embodiment, referring to fig. 2, an embodiment of the present disclosure further provides a people flow rate detection apparatus 20, including:
the system comprises an acquisition module 201, a processing module and a processing module, wherein the acquisition module is used for acquiring multiple frames of images corresponding to a preset area, and the preset area comprises a target area;
an extracting module 202, configured to extract a key area image of a target pedestrian from the preset area image including the target pedestrian in each frame;
the determining module 203 is configured to determine coordinates of an image area corresponding to a key part of the target pedestrian in a reference plane coordinate system by using a plane coordinate system corresponding to the preset area image as the reference plane coordinate system;
a judging module 204, configured to judge whether a coordinate of an image area corresponding to the key portion of the target pedestrian exceeds a coordinate set of the image area corresponding to the target area, and judge whether a duration of the key portion of the target pedestrian in the target area is matched with a preset threshold;
and if the coordinates corresponding to the key part image of the target pedestrian exceed the coordinate set corresponding to the target area image and the time of the key part of the target pedestrian in the target area image is matched with a preset threshold value, determining that the target pedestrian passes through the target area, and updating the personnel flow of the target area.
If the coordinate corresponding to the key position image of the target pedestrian does not exceed the coordinate set corresponding to the image of the target area or the time that the key position of the target pedestrian is located in the image of the target area is not matched with a preset threshold value, determining that the target pedestrian does not cross the target area, and forbidding updating the flow of the people in the target area.
The apparatus shown in fig. 2 may correspondingly execute the content in the above method embodiment, and details of the part not described in detail in this embodiment refer to the content described in the above method embodiment, which is not described again here.
Referring to fig. 3, an embodiment of the present disclosure also provides an electronic device 30, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of people flow detection in the above method embodiments.
The disclosed embodiments also provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the human flow detection method in the foregoing method embodiments.
The disclosed embodiments also provide a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the method of human flow detection in the aforementioned method embodiments.
Referring now to FIG. 3, a schematic diagram of an electronic device 30 suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., car navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 3, the electronic device 30 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data necessary for the operation of the electronic apparatus 30 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Generally, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touch pad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage devices 308 including, for example, magnetic tape, hard disk, etc.; and a communication device 309. The communication means 309 may allow the electronic device 30 to communicate wirelessly or by wire with other devices to exchange data. While the figures illustrate an electronic device 30 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication means 309, or installed from the storage means 308, or installed from the ROM 302. The computer program, when executed by the processing device 301, performs the above-described functions defined in the methods of the embodiments of the present disclosure.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. 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 of the computer readable storage medium may include, but are not limited to: 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 present disclosure, 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. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either 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: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring at least two internet protocol addresses; sending a node evaluation request comprising the at least two internet protocol addresses to node evaluation equipment, wherein the node evaluation equipment selects the internet protocol addresses from the at least two internet protocol addresses and returns the internet protocol addresses; receiving an internet protocol address returned by the node evaluation equipment; wherein the obtained internet protocol address indicates an edge node in the content distribution network.
Alternatively, the computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: receiving a node evaluation request comprising at least two internet protocol addresses; selecting an internet protocol address from the at least two internet protocol addresses; returning the selected internet protocol address; wherein the received internet protocol address indicates an edge node in the content distribution network.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, 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 latter scenario, 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).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a unit does not in some cases constitute a limitation of the unit itself, for example, the first retrieving unit may also be described as a "unit for retrieving at least two internet protocol addresses".
It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof.
The above description is only for the specific embodiments of the present disclosure, but the scope of the present disclosure is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present disclosure should be covered within the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (8)
1. A people flow detection method is characterized by comprising the following steps:
acquiring multiple frames of images corresponding to a preset area, wherein the preset area comprises a target area;
extracting a key region image of the target pedestrian from the preset region image containing the target pedestrian in each frame;
calculating to obtain an optimal face image according to the key part image of each frame including the target pedestrian; judging whether the optimal face image is matched with a preset face library or not, and if the optimal face image is matched with the preset face library or not, forbidding the coordinate calculation of the target pedestrian; if the optimal face image is not matched with a preset face library, calculating the coordinates of the target pedestrian; the preset face library is an optimal face image set corresponding to all pedestrians which are determined to pass through the target area in the prior personnel flow detection operation;
determining the coordinates of the image area corresponding to the key part of the target pedestrian in a reference plane coordinate system by taking a plane coordinate system corresponding to the preset area image as the reference plane coordinate system;
judging whether the coordinates of the image area corresponding to the key part of the target pedestrian exceed the coordinate set of the image area corresponding to the target area, and judging whether the time length of the key part of the target pedestrian in the target area is matched with a preset threshold value;
if the coordinates corresponding to the key part image of the target pedestrian exceed the coordinate set corresponding to the image of the target area and the time of the key part of the target pedestrian in the image of the target area is matched with a preset threshold value, determining that the target pedestrian passes through the target area, and updating the personnel flow of the target area;
if the coordinate corresponding to the key part image of the target pedestrian does not exceed the coordinate set corresponding to the image of the target area or the time that the key part of the target pedestrian is located in the image of the target area is not matched with a preset threshold value, determining that the target pedestrian does not cross the target area, and forbidding updating of the personnel flow of the target area.
2. The method of claim 1, wherein the face library is a face library formed in a current detection period, and the face library is emptied after each detection period.
3. The method according to claim 1, wherein the reference plane coordinate system is a plane coordinate system established with a target pixel point of the preset area image as an origin, each base coordinate point in the reference plane coordinate system corresponds to each pixel point of the preset area image, and the target pixel point is any one pixel point of the preset area image.
4. The method according to claim 3, wherein the step of determining the coordinates corresponding to the image of the key location of the target pedestrian in each frame of image of the preset area comprises:
and comparing the previously extracted key part bitmap pixel points of each frame of the target pedestrian with the origin to obtain the plane coordinates of the key part bitmap image of each frame of the target pedestrian.
5. The method according to any one of claims 1 to 4, wherein the target pedestrian key location image comprises a hand image, a leg image, and a face image.
6. The method according to claim 1, wherein before the step of determining whether the duration of the time that the key part of the target pedestrian is in the target area matches a preset threshold, the method further comprises:
calculating the time of a preset sample person passing through the target area;
and calculating the average crossing time as the preset threshold according to the time of all the sample personnel passing through the target area.
7. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the human traffic detection method of any one of the preceding claims 1-6.
8. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the people flow detection method of any one of the preceding claims 1-6.
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