CN111444926A

CN111444926A - Radar-based regional people counting method, device, equipment and storage medium

Info

Publication number: CN111444926A
Application number: CN202010200465.7A
Authority: CN
Inventors: 阳召成; 鲍润晗
Original assignee: Shenzhen University
Current assignee: Shenzhen University
Priority date: 2020-03-20
Filing date: 2020-03-20
Publication date: 2020-07-24
Anticipated expiration: 2040-03-20
Also published as: CN111444926B

Abstract

The embodiment of the invention discloses a radar-based regional people counting method, a radar-based regional people counting device, radar-based regional people counting equipment and a storage medium. The radar-based regional people counting method comprises the following steps: acquiring and storing first radar data without a living body in a first preset time of a target area; establishing a first monitoring background model according to the first radar data; acquiring and storing second radar data of the target area; and counting the first number of people in the target area according to the first monitoring background model and the second radar data. The embodiment of the invention realizes the reduction of the working environment requirement and the calculation resource requirement when counting the number of people in the area.

Description

Radar-based regional people counting method, device, equipment and storage medium

Technical Field

The embodiment of the invention relates to an image processing technology, in particular to a radar-based regional people counting method, device, equipment and storage medium.

Background

With the development of technologies such as the internet of things and the 5G, the intelligent building, the intelligent home, the intelligent security and the like are also rapidly developed. For the above aspect, people information of the region of interest is a very important type of basic data information. The information can be used for monitoring crowd abnormity, region security, public resource scheduling and other application aspects. The statistical problem of the number of regional people has entered the visual field of researchers for a long time, many researchers (engineering users) develop many people statistical systems based on different principles according to different sensors, and the common people statistical methods are mainly a method based on section type detection and a method based on regional type detection.

The section-based detection method mainly comprises a three-roller gate method, an infrared correlation method and a gravity induction method. The triple-roller gate method is used for counting the number of people by using a physical mechanical method. The system can accurately count the number of people passing in and out of a certain inlet and outlet, the side surface reflects the number density of people in a certain area, but the system is not suitable for the area with large flow of people and has poor experience; the infrared correlation method is used for counting the number of people by detecting the infrared blocking condition generated when a human body passes through a correlation area. The system can detect the number of people passing through a certain section, but cannot detect the direction, and has poor accuracy when people flow is large and is influenced by the environmental temperature; the gravity sensing method estimates the number of people and counts the people by detecting the gravity change of a certain section, but the detection precision is limited due to the influence of environmental factors, and the installation and the maintenance are inconvenient.

The method based on the area type detection mainly comprises an optical sensor vision method, an active infrared imaging method, a radio frequency identification method and a wireless local area network method. The optical sensor vision method can perform regional people counting by analyzing the human images. However, the method is influenced by illumination and geographical environment conditions, relates to privacy problems, and needs more computing and storage resources; the active infrared imaging method can acquire information similar to an optical sensor, and can acquire higher angular resolution to count the number of people in the region. However, the detection distance under strong light is shortened due to the influence of the ambient temperature, and more calculation resources are also needed; the RFID method is to count the number of people by detecting an RFID tag carried by a human body. This approach lacks convenience in many random life scenarios; the wireless local area network approach estimates the number of people in an area by detecting channel state information (for calculating power or other information). Since physical characteristics of a human body cannot be detected, its performance is limited and it is more susceptible to external signals.

In summary, various problems still exist in the statistical method for the number of people in the area, and particularly, the problems that the method is ubiquitous and needs to be solved urgently are the high requirements for detecting the working environment of the equipment and the high occupation of computing resources.

Disclosure of Invention

The embodiment of the invention provides a radar-based regional people counting method, device, equipment and storage medium, which are used for reducing working environment requirements and computing resource requirements when regional people are counted.

To achieve the purpose, the embodiment of the invention provides a radar-based regional people counting method, which comprises the following steps:

acquiring and storing first radar data without a living body in a first preset time of a target area;

establishing a first monitoring background model according to the first radar data;

acquiring and storing second radar data in a second preset time of the target area;

and counting the first number of people in the target area according to the first monitoring background model and the second radar data.

Further, the acquiring and storing second radar data in a second preset time of the target area includes:

and acquiring and storing second radar data of the target area within second preset time, and taking the second radar data without a living body within the second preset time of the target area as third radar data for additional storage.

Further, the counting a first person number of the target area according to the first monitoring background model and the second radar data comprises:

after the third radar data are obtained, if the time of the target area without a living body continuously exceeds a third preset time, establishing a second monitoring background model according to the third radar data;

and counting the number of people in a second area of the target area according to the second monitoring background model and second radar data.

Further, the establishing a first monitoring background model according to the first radar data includes:

merging each frame data of the first radar data by fixing adjacent distance units to obtain first merged data;

after performing module and logarithm operation on the first combined data, performing mean value and variance iteration based on the first monitoring background model to obtain first background data;

and establishing a first monitoring background model according to the first background data.

Further, the counting the first person number of the target area according to the first monitoring background model and the second radar data comprises:

obtaining a first three-dimensional feature map according to the first monitoring background model and the second radar data;

obtaining a first STFT feature vector according to the second radar data;

and putting the first three-dimensional feature map and the first STFT feature vector into a pre-trained neural network model to count the first number of people in the target area.

Further, the obtaining a first three-dimensional feature map according to the first monitoring background model and the second radar data includes:

performing clutter suppression processing on each frame of data of the second radar data to obtain fourth radar data;

merging each frame data of the fourth radar data by fixing adjacent distance units to obtain second merged data;

carrying out fixed-scale potential target peak detection on the second combined data, and obtaining a first two-dimensional characteristic diagram after linear amplification and amplitude limiting operation;

noise removal based on a preset noise threshold is carried out on the second combined data, and a second two-dimensional characteristic diagram is obtained after linear amplification and amplitude limiting operation;

carrying out abnormal value iterative detection on each frame of data of the second radar data according to the first monitoring background model, and obtaining a third two-dimensional characteristic diagram after linear amplification and amplitude limiting operation;

and obtaining a first three-dimensional characteristic diagram according to the first two-dimensional characteristic diagram, the second two-dimensional characteristic diagram and the third two-dimensional characteristic diagram.

Further, the obtaining the first STFT feature vector according to the second radar data includes:

performing short-time Fourier transform on the fourth radar data to obtain a first power spectrum;

normalizing the first power spectrum to obtain a first power spectrum vector;

adding a sum of the values of the first power spectrum to the first power spectrum vector to obtain a first STFT feature vector.

On one hand, the embodiment of the invention also provides a radar-based regional people counting device, which comprises:

the data acquisition module is used for acquiring and storing first radar data without a living body in a first preset time of a target area;

the model establishing module is used for establishing a first monitoring background model according to the first radar data;

the data acquisition module is further used for acquiring and storing second radar data in a second preset time of the target area;

and the people counting module is used for counting the first people in the target area according to the first monitoring background model and the second radar data.

On the other hand, the embodiment of the invention also provides radar-based regional people counting equipment, which comprises: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement a method as provided by any embodiment of the invention.

In yet another aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the method provided in any embodiment of the present invention.

According to the embodiment of the invention, first radar data without a living body in a first preset time of a target area is obtained and stored; establishing a first monitoring background model according to the first radar data; acquiring and storing second radar data in a second preset time of the target area; and counting the first person number of the target area according to the first monitoring background model and the second radar data, solving the problems of high requirement on the working environment of the detection equipment and high occupation of computing resources in the existing area person number counting method, and realizing the effect of reducing the working environment requirement and the computing resource requirement when counting the number of people in the area.

Drawings

FIG. 1 is a schematic flow chart of a radar-based region people counting method according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart of a radar-based region people counting method according to a second embodiment of the present invention;

FIG. 3 is a schematic flow chart of a radar-based region people counting method according to a third embodiment of the present invention;

FIG. 4 is a schematic flowchart of a radar-based region people counting method according to a third embodiment of the present invention;

FIG. 5 is a schematic structural diagram of an area people counting device based on radar according to a fourth embodiment of the present invention;

fig. 6 is a schematic structural diagram of a radar-based device for counting people in an area according to a fifth 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 for purposes of illustration and not limitation. 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.

Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. A process may be terminated when its operations are completed, but may have additional steps not included in the figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

Furthermore, the terms "first," "second," and the like may be used herein to describe various orientations, actions, steps, elements, or the like, but the orientations, actions, steps, or elements are not limited by these terms. These terms are only used to distinguish one direction, action, step or element from another direction, action, step or element. For example, a first module may be termed a second module, and, similarly, a second module may be termed a first module, without departing from the scope of the present application. The first module and the second module are both modules, but they are not the same module. The terms "first", "second", etc. are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the embodiments of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.

Example one

As shown in fig. 1, a first embodiment of the present invention provides a radar-based area people counting method, including:

and S110, acquiring and storing first radar data without a living body in a first preset time of a target area.

And S120, establishing a first monitoring background model according to the first radar data.

In this embodiment, a low power consumption UWB pulse radar system is used to collect data, and the radar system is placed at different preset positions, thereby acquiring radar data. First, a plurality of target areas are obtained through the radar system, the first radar data are radar data without a living body in a first preset time in the target areas, the first preset time can be 20 seconds, and exemplarily, the radar data of the target areas with a still picture of 20 seconds are collected through the radar system. And uploading the first radar data to a processing terminal through a data line or a wireless communication module after the first radar data is acquired. At this time, the processing terminal can establish a first monitoring background model according to the first radar data.

And S130, acquiring and storing second radar data in a second preset time of the target area.

And S140, counting the first number of people in the target area according to the first monitoring background model and the second radar data.

In this embodiment, after the first monitoring background model is established, radar data can be formally obtained for people counting, second radar data in a second preset time of the target area is obtained and uploaded to the processing terminal for storage, and then the processing terminal can count the first people in the target area according to the first monitoring background model and the second radar data, wherein the second preset time can be 3 seconds, and the first radar data and the second radar data can be stored, so that convenience is brought to follow-up and analysis after the fact.

Example two

As shown in fig. 2, a second embodiment of the present invention provides a radar-based regional people counting method, and further explanation and explanation are provided on the basis of the first embodiment of the present invention, where the method includes:

s210, first radar data of no living body in a first preset time of the target area are obtained and stored.

S220, merging each frame data of the first radar data by fixing adjacent distance units to obtain first merged data.

And S230, after the first combined data is subjected to modulus and logarithm taking, performing mean value and variance iteration based on the first monitoring background model to obtain first background data.

S240, establishing a first monitoring background model according to the first background data.

In this embodiment, after the first radar data is obtained, a series of signal preprocessing needs to be performed on the first radar data, specifically, each frame of data of the first radar data is combined by fixed adjacent distance units frame by frame to obtain first combined data of each frame of data, then the first combined data is subjected to modulo logarithm, a mean value and a variance iteration based on a first monitoring background model is performed to obtain first background data, and finally the first monitoring background model is established according to the first background data.

And S250, obtaining a first three-dimensional characteristic diagram according to the first monitoring background model and the second radar data.

And S260, obtaining a first STFT feature vector according to the second radar data.

S270, putting the first three-dimensional feature map and the first STFT feature vector into a pre-trained neural network model to count the first number of people in the target area.

In this embodiment, a first three-dimensional feature map may be obtained from the first monitored background model and the second radar data, a first STFT (short-time Fourier transform) feature vector may be obtained from the second radar data, a pre-trained neural network model may be a convolutional neural network model, specifically including nine 2D convolutional layers, four pooling layers, three fully-connected layers, and one sorting layer, the sorting layer may be a Softmax sorting layer, wherein the 2D convolutional layers and the fully-connected layers use Re L U (Rectised 5 input Unit, linear rectification function) activation function, but the convolutional cores and the convolutional operation steps are different, the pooling layer kernel size and the operation step size of the pooling layer are L M L M and stride Nm., the data flow direction of the pooling layer is a 2D convolutional layer, the convolutional layer kernel size, and the operation step size are L M L M, and the stride 365924M 3627M 3, the convolutional layer kernel size, the Stride 2F 3, the Stride kernel size, the Strobe 3, the Strobe 3627, the convolutional layer kernel size, the Strobe 363, the target convolutional layer size, the Strobe 3, the Strobe 363, the convolutional layer size, the Strobe 363, the Strobe 3, the Strobe 3627, the Strobe 363, the convolutional layer, the Strobe 363, the S3, the S363, the S3, the S3627, the S363, the S3, the S363, the S3, the S363, the S3.

And S280, acquiring and storing second radar data of the target area within second preset time, and taking the second radar data without a living body within the second preset time of the target area as third radar data for additional storage.

And S290, after the third radar data are obtained, if the time of the target area without the living body continuously exceeds a third preset time, establishing a second monitoring background model according to the third radar data.

And S300, counting the number of people in a second area of the target area according to the second monitoring background model and second radar data.

In this embodiment, when the second radar data of the target area is acquired, the second radar data without a living body in the target area within the second preset time may be additionally stored as third radar data, where the second preset time may be 1 to 3 seconds, for example, 2 seconds, so that after the first person number of the target area is obtained through statistics, further optimization may be performed, and after the third radar data is acquired, if the time when the living body is continuously absent in the target area exceeds the third preset time, that is, when the third radar data is continuously acquired for more than the third preset time, a second monitoring background model may be further established according to the third radar data, it should be noted that, as long as the time when the living body is present occurs within the third preset time, the third radar data is cleared, and the radar data storage and timing are restarted. And the third preset time can be 5-15 seconds, for example, 10 seconds, and after the second monitoring background model is obtained, counting the number of people in the second area of the target area according to the second monitoring background model and the second radar data. Preferably, steps S290-S300 in the first embodiment of the present invention may be repeatedly performed to continuously optimize the monitoring background model and count the number of people with the truest population.

EXAMPLE III

As shown in fig. 3 and 4, a third embodiment of the present invention provides a radar-based area people counting method, and the third embodiment of the present invention is further explained and explained on the basis of the second embodiment of the present invention, and as shown in fig. 3, step S250 in the method specifically includes:

and S251, performing clutter suppression processing on each frame of data of the second radar data to obtain fourth radar data.

S252, merging each frame data of the fourth radar data by the fixed adjacent distance unit to obtain second merged data.

And S253, carrying out potential target peak detection with a fixed scale on the second combined data, and obtaining a first two-dimensional characteristic diagram after linear amplification and amplitude limiting operation.

And S254, removing noise based on a preset noise threshold on the second combined data, and performing linear amplification and amplitude limiting operation to obtain a second two-dimensional characteristic diagram.

And S255, carrying out abnormal value iterative detection on each frame of data of the second radar data according to the first monitoring background model, and obtaining a third two-dimensional characteristic diagram after linear amplification and amplitude limiting operation.

And S256, obtaining a first three-dimensional feature map according to the first two-dimensional feature map, the second two-dimensional feature map and the third two-dimensional feature map.

In this embodiment, a specific process of obtaining the first three-dimensional feature map from the first monitoring background model and the second radar data may be as follows: each frame of data of the second radar data is first processed by clutter suppression frame by frame to obtain fourth radar data, then, each frame data of the fourth radar data is merged by the fixed adjacent distance units frame by frame to obtain second merged data, after the second merged data which is merged by clutter suppression processing and the fixed adjacent distance units is obtained, the second merged data can be subjected to potential target peak detection with a fixed scale, a first two-dimensional feature map is obtained after linear amplification and amplitude limiting operation, noise removal based on a preset noise threshold is continuously performed on the second merged data, a second two-dimensional feature map can be obtained after linear amplification and amplitude limiting operation, and then carrying out iterative detection on abnormal values of each frame of data of the second radar data frame by frame according to the first monitoring background model, and obtaining a third two-dimensional characteristic diagram after linear amplification and amplitude limiting operations. And finally, obtaining a first three-dimensional characteristic diagram from the first two-dimensional characteristic diagram, the second two-dimensional characteristic diagram and the third two-dimensional characteristic diagram.

As shown in fig. 4, step S260 in the method specifically includes:

and S261, performing short-time Fourier transform on the fourth radar data to obtain a first power spectrum.

S262, normalizing the first power spectrum to obtain a first power spectrum vector.

S263, adding the numerical sum of the first power spectrum to the first power spectrum vector to obtain a first STFT feature vector.

In this embodiment, the specific process of obtaining the first STFT feature vector from the second radar data may be: and performing short-time Fourier transform on the fourth radar data obtained in the step S251 to obtain a first power spectrum, normalizing the first power spectrum to obtain a first power spectrum vector, and adding the sum of the numerical values of the first power spectrum to the first power spectrum vector to obtain a first STFT feature vector.

Example four

As shown in fig. 5, a radar-based region population counting device 100 is provided in the fourth embodiment of the present invention, and the radar-based region population counting device 100 provided in the third embodiment of the present invention can execute the radar-based region population counting method provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method. The radar-based area people counting apparatus 100 includes a data acquisition module 200, a model building module 300, and a people counting module 400.

Specifically, the data acquisition module 200 is configured to acquire and store first radar data of a target area without a living body within a first preset time; the model establishing module 300 is configured to establish a first monitoring background model according to the first radar data; the data acquisition module 200 is further configured to acquire and store second radar data in a second preset time of the target area; the people counting module 400 is configured to count a first number of people in the target area according to the first monitoring background model and the second radar data.

In this embodiment, the data obtaining module 200 is specifically configured to obtain and store second radar data in the second preset time of the target area, and additionally store the second radar data without a living body in the second preset time of the target area as third radar data. The model building module 300 is specifically configured to perform merging of fixed adjacent distance units on each frame of data of the first radar data to obtain first merged data; after performing module and logarithm operation on the first combined data, performing mean value and variance iteration based on the first monitoring background model to obtain first background data; and establishing a first monitoring background model according to the first background data. The people counting module 400 is specifically configured to obtain a first three-dimensional feature map according to the first monitoring background model and the second radar data; obtaining a first STFT feature vector according to the second radar data; and putting the first three-dimensional feature map and the first STFT feature vector into a pre-trained neural network model to count the first number of people in the target area. The people counting module 400 is further configured to perform clutter suppression processing on each frame of data of the second radar data to obtain fourth radar data; merging each frame data of the fourth radar data by fixing adjacent distance units to obtain second merged data; carrying out fixed-scale potential target peak detection on the second combined data, and obtaining a first two-dimensional characteristic diagram after linear amplification and amplitude limiting operation; noise removal based on a preset noise threshold is carried out on the second combined data, and a second two-dimensional characteristic diagram is obtained after linear amplification and amplitude limiting operation; carrying out abnormal value iterative detection on each frame of data of the second radar data according to the first monitoring background model, and obtaining a third two-dimensional characteristic diagram after linear amplification and amplitude limiting operation; and obtaining a first three-dimensional characteristic diagram according to the first two-dimensional characteristic diagram, the second two-dimensional characteristic diagram and the third two-dimensional characteristic diagram. The people counting module 400 is further specifically configured to perform short-time fourier transform on the fourth radar data to obtain a first power spectrum; normalizing the first power spectrum to obtain a first power spectrum vector; adding a sum of the values of the first power spectrum to the first power spectrum vector to obtain a first STFT feature vector.

Further, the radar-based region people counting device 100 further includes a secondary counting module 500, where the secondary counting module 500 is configured to, after the third radar data is obtained, if the time for the target region to continuously have no living body exceeds a third preset time, establish a second monitoring background model according to the third radar data; and counting the number of people in a second area of the target area according to the second monitoring background model and second radar data.

EXAMPLE five

Fig. 6 is a schematic structural diagram of a radar-based region people counting computer device 12 according to a fifth embodiment of the present invention. FIG. 6 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention. The computer device 12 shown in FIG. 6 is only an example and should not bring any limitations to the functionality or scope of use of embodiments of the present invention.

As shown in FIG. 6, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.

Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

Computer device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.

The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, and commonly referred to as a "hard drive"). Although not shown in FIG. 6, 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 bus 18 by one or more data media interfaces. Memory 28 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 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 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 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.

Computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and may also communicate with one or more devices that enable a user to interact with the computer device 12, and/or with any devices (e.g., network card, modem, etc.) that enable the computer device 12 to communicate with one or more other computing devices, such communication may occur via input/output (I/O) interfaces 22. moreover, computer device 12 may also communicate with one or more networks (e.g., a local area network (L AN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via network adapter 20. As shown, network adapter 20 communicates with other modules of computer device 12 via bus 18. it should be appreciated that, although not shown, other hardware and/or software modules may be used in conjunction with computer device 12, including, but not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing the methods provided by the embodiments of the present invention:

EXAMPLE six

The sixth 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 methods provided in all the embodiments of the present invention of the present application:

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 aspects 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 + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages.

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

1. A radar-based regional people counting method is characterized by comprising the following steps:

2. The method of claim 1, wherein the acquiring and storing second radar data within a second preset time of the target area comprises:

3. The method of claim 2, wherein said counting a first number of persons for the target region based on the first monitored background model and second radar data comprises:

4. The method of claim 1, wherein establishing a first monitoring context model from the first radar data comprises:

5. The method of claim 1, wherein said counting a first person for the target region from the first monitored background model and second radar data comprises:

obtaining a first STFT feature vector according to the second radar data;

6. The method of claim 5, wherein the deriving a first three-dimensional feature map from the first monitored background model and second radar data comprises:

7. The method of claim 6, wherein the deriving a first STFT feature vector from the second radar data comprises:

normalizing the first power spectrum to obtain a first power spectrum vector;

8. A radar-based area people counting device is characterized by comprising:

9. A radar-based regional people counting device, comprising:

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 the method of any one of claims 1-7.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-7.