Pedestrian information detection method, device and electronic equipment

Abstract

The present disclosure provides a method, device and electronic device for detecting pedestrian information, and relates to the field of computer application technology. The method includes: obtaining an observation data matrix of a ground sensor; the observation data matrix is ​​generated by multiple ground sensors according to an excitation signal at the same frame time; calculating a residual matrix corresponding to the observation data matrix according to a pre-stored clutter scene matrix, and performing target detection on the residual matrix to obtain pedestrian information on the intelligent ground. The pedestrian information detection method, device and electronic device provided by the present disclosure can eliminate clutter signals in the observation data matrix, and then obtain a residual matrix including only pedestrian signals, thereby avoiding the influence of clutter on pedestrian signals, and at the same time, reducing the amount of calculation, which helps to improve the accuracy of detection.

Description

Technical Field

[0001] The present disclosure relates to the technical field of computer applications, and in particular to a pedestrian information detection method, device and electronic equipment. Background Art

[0002] Smart ground relies on a dot matrix sensor network laid on the ground to sense the location of the target of interest. For practical applications, after laying the smart ground, there are other targets on the ground, such as furniture, which are not of interest to us. In applications, the targets of interest are usually pedestrians, and we call the fixed targets of no interest clutter. When detecting pedestrians based on the above smart ground, these clutters often interfere with the detection process and affect the accuracy of the detection. Summary of the invention

[0003] In view of this, the purpose of the present disclosure is to provide a pedestrian information detection method, device and electronic device to alleviate the above technical problems.

[0004] In a first aspect, an embodiment of the present disclosure provides a method for detecting pedestrian information, comprising: obtaining an observation data matrix of a ground sensor; wherein the ground sensor is arranged on an intelligent ground according to a preset dot matrix pattern, and is used to generate an excitation signal when stimulated; the observation data matrix is ​​generated by multiple ground sensors according to the excitation signal at the same frame time; a residual matrix corresponding to the observation data matrix is ​​calculated according to a pre-stored clutter scene matrix, wherein the clutter scene matrix is ​​a data matrix generated according to the excitation signal of the ground sensor during an unmanned period; and target detection is performed on the residual matrix to obtain pedestrian information on the intelligent ground.

[0005] In combination with the first aspect, an embodiment of the present disclosure provides a first possible implementation of the first aspect, wherein the step of calculating the residual matrix corresponding to the observation data matrix based on the pre-stored clutter scene matrix includes: subtracting the element value at the corresponding position in the clutter scene matrix from each element value in the observation data matrix to obtain the residual element; and generating the residual matrix corresponding to the observation data matrix based on the residual elements.

[0006] In combination with the first possible implementation of the first aspect, an embodiment of the present disclosure provides a second possible implementation of the first aspect, wherein, in one possible implementation, the above-mentioned step of performing target detection on the remaining matrix to obtain pedestrian information on the smart ground includes: calculating a threshold value corresponding to the remaining matrix based on multiple remaining elements included in the remaining matrix; and performing 0-1 detection on the remaining matrix based on the threshold value to obtain pedestrian information on the smart ground.

[0007] In combination with the second possible implementation of the first aspect, an embodiment of the present disclosure provides a third possible implementation of the first aspect, wherein, in one possible implementation, the step of calculating the threshold value corresponding to the residual matrix based on the multiple residual elements included in the residual matrix includes: randomly selecting a preset number of independent areas in the residual matrix; the independent area includes multiple residual elements; calculating the mean of the residual elements included in each independent area, and selecting the minimum value of the mean as the noise level value of the residual matrix; multiplying the noise level value by a preset threshold coefficient to obtain the threshold value.

[0008] In combination with the second possible implementation of the first aspect, the embodiment of the present disclosure provides a fourth possible implementation of the first aspect, wherein the above-mentioned step of performing 0-1 detection on the remaining matrix based on the threshold value to obtain pedestrian information on the intelligent ground includes: for each remaining element included in the remaining matrix, performing the following marking operation: determining whether the remaining element is greater than the threshold value; if so, marking the position of the remaining element in the remaining matrix as 1; if not, marking the position of the remaining element in the remaining matrix as 0; generating a marking matrix corresponding to the remaining matrix according to the result of the marking operation; and counting pedestrian information on the intelligent ground based on the marking matrix.

[0009] In combination with the second possible implementation of the fourth aspect, the embodiment of the present disclosure provides a fifth possible implementation of the first aspect, wherein the above-mentioned step of counting pedestrian information on the smart ground based on the marking matrix includes: counting the number of areas connected by elements marked as 1 in the marking matrix, and determining the number as the number of pedestrians on the current smart ground; and / or, counting the relative positions of areas connected by elements marked as 1 in the marking matrix in the marking matrix, and determining the relative positions as the position information of pedestrians on the current smart ground.

[0010] In combination with the first aspect, an embodiment of the present disclosure provides a sixth possible implementation of the first aspect, wherein the above method also includes: obtaining excitation signals of multiple frames of ground sensors in unmanned periods, and generating a detection signal matrix of the ground sensor in each frame based on the excitation signals, wherein each element in the detection signal matrix corresponds to an excitation signal of a ground sensor; calculating the mean of the elements at the same position in the detection signal matrix of each frame to obtain the mean signal at that position; traversing each element in the detection signal matrix, calculating the mean signal at that position, and generating a clutter scene matrix based on the mean signal corresponding to each position.

[0011] In a second aspect, an embodiment of the present disclosure provides a pedestrian information detection device, comprising: an acquisition module, used to acquire an observation data matrix of a ground sensor; wherein the ground sensor is arranged on the smart ground according to a preset dot matrix pattern, and is used to generate an excitation signal when stimulated; the observation data matrix is ​​generated by multiple ground sensors according to the excitation signal at the same frame time; a calculation module, used to calculate a residual matrix corresponding to the observation data matrix according to a pre-stored clutter scene matrix, wherein the clutter scene matrix is ​​a data matrix generated according to the excitation signal of the ground sensor during an unmanned period; a detection module, used to perform target detection on the residual matrix to obtain pedestrian information on the smart ground.

[0012] The embodiments of the present disclosure bring the following beneficial effects:

[0013] The pedestrian information detection method, device and electronic device provided by the embodiments of the present disclosure can obtain the observation data matrix of the ground sensor, and calculate the residual matrix corresponding to the observation data matrix according to the pre-stored clutter scene matrix, and then perform target detection on the residual matrix to obtain pedestrian information on the intelligent ground. Since the above-mentioned clutter scene matrix is ​​a data matrix generated according to the excitation signal of the ground sensor during the unmanned period, when the residual matrix is ​​calculated according to the clutter scene matrix, the clutter signal in the observation data matrix can be eliminated, and then the residual matrix including only the pedestrian signal is obtained, avoiding the influence of clutter on the pedestrian signal, and at the same time, reducing the amount of calculation, which helps to improve the accuracy of detection.

[0014] Other features and advantages of the present disclosure will be described in the following description, and partly become apparent from the description, or understood by practicing the present disclosure. The purpose and other advantages of the present disclosure are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0015] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the specific embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 A flowchart of a pedestrian information detection method provided by an embodiment of the present disclosure;

[0018] Figure 2A flowchart of another pedestrian information detection method provided by an embodiment of the present disclosure;

[0019] Figure 3 A schematic diagram of a clutter scene matrix provided in an embodiment of the present disclosure;

[0020] Figure 4 A schematic diagram of an observation data matrix provided in an embodiment of the present disclosure;

[0021] Figure 5 A schematic diagram of a residual matrix provided in an embodiment of the present disclosure;

[0022] Figure 6 A schematic diagram of a pedestrian information detection result provided by an embodiment of the present disclosure;

[0023] Figure 7 A schematic diagram of the structure of a pedestrian information detection device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0025] Usually, for smart ground with a dot matrix sensor network, pedestrian information can be detected, such as whether someone has entered the smart ground, or how many people have entered the area where the smart ground is located, etc., to facilitate the detection of pedestrian information. However, there are often other targets on the ground, such as furniture, etc., which are not of interest to us. How to remove fixed targets other than pedestrians while retaining the detection of pedestrians is a difficulty in smart ground signal processing. At present, there is no method for eliminating fixed clutter based on smart ground. Based on this, a pedestrian information detection method, device and electronic device provided in the embodiments of the present disclosure can alleviate the above problems.

[0026] To facilitate understanding of this embodiment, a pedestrian information detection method disclosed in the embodiment of the present disclosure is first introduced in detail.

[0027] In a possible implementation, the embodiment of the present disclosure provides a method for detecting pedestrian information. The method may be applied to a server. The server, as a back-end signal processing system of the smart ground, may obtain the signals collected by the dot matrix sensor network of the smart ground, thereby performing a pedestrian information detection process. Specifically, Figure 1A flowchart of a pedestrian information detection method is shown, the method comprising the following steps:

[0028] Step S102, obtaining the observation data matrix of the ground sensor;

[0029] Among them, the above-mentioned ground sensors are arranged on the smart ground according to a preset dot matrix pattern to form a dot matrix sensor network of the smart ground, which is used to generate an excitation signal when stimulated; specifically, the above-mentioned ground sensors can be pressure sensors, or infrared sensors, etc. Taking the pressure sensor as an example, when pedestrians enter the area where the smart ground is located, stepping on the smart ground can stimulate the pressure sensor. After the pressure sensor is stimulated, it can generate an excitation signal. When the ground sensors are arranged on the ground according to a preset arrangement, a sensor array can be formed. The excitation signals generated by each ground sensor can be combined together to form an observation data matrix, which can be transmitted to the connected back-end signal processing system, and then the pedestrian information detection method provided by the embodiment of the present disclosure is executed.

[0030] Specifically, the above observation data matrix is ​​generated by multiple ground sensors according to the excitation signal at the same frame time. Therefore, each element of the observation data matrix corresponds to a ground sensor at a corresponding position of the smart ground.

[0031] Step S104, calculating the residual matrix corresponding to the observation data matrix according to the pre-stored clutter scene matrix;

[0032] Among them, the clutter scene matrix in the embodiment of the present disclosure is a data matrix generated according to the excitation signal of the ground sensor during the unmanned period.

[0033] Usually, the signals of ground sensors can be collected during unmanned periods to generate the above-mentioned clutter scene matrix. The purpose is to obtain signals during unmanned periods, because the signals on the intelligent ground during unmanned periods are all generated by stationary fixed targets, that is, clutter signals. If there are people, it will affect the judgment. Therefore, the purpose of recording signals during unmanned periods is to ensure that the signals of fixed targets can be accurately collected.

[0034] Step S106: perform target detection on the remaining matrix to obtain pedestrian information on the smart ground.

[0035] Among them, since the residual matrix is ​​calculated based on the above-mentioned clutter scene matrix, the residual matrix is ​​a matrix that eliminates clutter signals and only contains useful information. If there is pedestrian information, it can be obtained through target detection. In addition, since clutter signals are eliminated during target detection, the amount of detection calculation can be effectively reduced.

[0036] Therefore, the pedestrian information detection method provided by the embodiment of the present disclosure can obtain the observation data matrix of the ground sensor, and calculate the residual matrix corresponding to the observation data matrix according to the pre-stored clutter scene matrix, and then perform target detection on the residual matrix to obtain pedestrian information on the intelligent ground. Since the above-mentioned clutter scene matrix is ​​a data matrix generated according to the excitation signal of the ground sensor during the unmanned period, when the residual matrix is ​​calculated according to the clutter scene matrix, the clutter signal in the observation data matrix can be eliminated, and then the residual matrix including only the pedestrian signal is obtained, avoiding the influence of clutter on the pedestrian signal, and at the same time, reducing the amount of calculation, which helps to improve the accuracy of detection.

[0037] In actual use, the data transmission time of the above-mentioned ground sensors can be set so that the sensors send data to the server at regular time intervals according to the same timing and form an observation data matrix, so that the server can obtain the observation data matrix and perform data processing.

[0038] In addition, a data acquisition method can also be set on the server side so that the server actively obtains observation data from ground sensors at certain time intervals and generates an observation data matrix. The specific data acquisition method can be set according to actual usage, and the embodiments of the present disclosure do not limit this.

[0039] Furthermore, the clutter scene matrix is ​​usually a data matrix pre-generated by the server and stored in a corresponding storage area. In order to make the clutter scene matrix universally applicable, a plurality of frames of data are usually selected during an unmanned period to calculate the average value of the excitation signal, and then the clutter scene matrix is ​​generated according to the average value. Specifically, the acquisition process of the clutter matrix in the embodiment of the present disclosure includes the following steps:

[0040] (1) obtaining excitation signals of multiple frames of ground sensors during unmanned periods, and generating a detection signal matrix of the ground sensors in each frame according to the excitation signals, wherein each element in the detection signal matrix corresponds to an excitation signal of a ground sensor;

[0041] (2) Calculate the mean of the elements at the same position in the detection signal matrix of each frame to obtain the mean signal at that position;

[0042] (3) Traverse each element in the detection signal matrix, calculate the mean signal at that position, and generate a clutter scene matrix based on the mean signal corresponding to each position.

[0043] For example, in the above (1), 10,000 frames of excitation signals can be obtained in chronological order during the unmanned period. At this time, a detection signal matrix can be generated for each frame, that is, 10,000 detection signal matrices are obtained. When the mean signal is calculated according to the above (2), the elements at the same position in the 10,000 detection signal matrices are selected to calculate the mean, which can be expressed as A(i, j) = (1 / 10000)(a1 ij +a2 ij +…+a10000 ij ), where A(i, j) represents the element in the i-th row and j-th column of the clutter scene matrix, and a1 ij 、a2 ij …a10000 ij Represents the element at the i-th row and j-th column position of each of the 10,000 detection signal matrices, that is, A(i, j) is a mean signal. After traversing the elements at each position in the detection signal matrix, the mean signal at each position can be obtained, and then the above-mentioned clutter scene matrix can be generated.

[0044] After obtaining the above clutter scene matrix, for each observation data matrix obtained by the server, the clutter can be removed by subtracting the observation data matrix from the clutter scene matrix to obtain the above residual matrix. Figure 1 On the basis of Figure 2 A flowchart of another pedestrian information detection method is also provided, and the calculation of the residual matrix and the target detection process are described in detail. Figure 2 As shown, the following steps are included:

[0045] Step S202, obtaining the observation data matrix of the ground sensor;

[0046] The above-mentioned ground sensors are arranged on the smart ground in a preset dot matrix pattern to form a dot matrix sensor network of the smart ground, which is used to generate an excitation signal when stimulated;

[0047] Specifically, the above-mentioned observation data matrix is ​​generally generated when pedestrians enter the smart floor and the ground sensors are stimulated. Therefore, the above-mentioned observation data matrix generally contains pedestrian information. In addition to pedestrian information, the observation matrix also contains clutter information, such as furniture, other fixed objects placed on the smart floor, etc., which constitute clutter signals of pedestrian information. In order to remove these clutter signals, the following steps S204 and S206 are usually used to perform denoising processing to obtain a residual matrix containing only pedestrian information.

[0048] Step S204, subtracting the element value at the corresponding position in the clutter scene matrix from each element value in the observation data matrix to obtain the remaining element;

[0049] Step S206, generating a residual matrix corresponding to the observation data matrix according to the remaining elements;

[0050] Specifically, since the above-mentioned clutter scene matrix is ​​a data matrix generated according to the excitation signal of the ground sensor in the unmanned period, the clutter scene matrix only includes clutter signals. In the above-mentioned step S204, the remaining elements obtained by subtracting the element value of the corresponding position in the clutter scene matrix from each element value in the observation data matrix are the elements after the clutter is removed, and the remaining matrix composed of the remaining elements is the matrix after the clutter signal is removed. Therefore, the subsequent steps S208 and S210 can be continued to perform target detection on the matrix after the clutter signal is removed to obtain pedestrian information on the smart ground.

[0051] Step S208, calculating a threshold value corresponding to the remaining matrix according to a plurality of remaining elements included in the remaining matrix;

[0052] Step S210: Perform 0-1 detection on the remaining matrix based on the threshold value to obtain pedestrian information on the smart ground.

[0053] Specifically, when calculating the threshold value, a preset number of independent regions are usually randomly selected in the residual matrix; the independent region includes multiple residual elements; then the mean of the residual elements included in each independent region is calculated, and the minimum value of the mean is selected as the noise level value of the residual matrix; the noise level value is multiplied by the preset threshold coefficient to obtain the threshold value.

[0054] For example, four independent regions at four positions in the residual matrix can be selected, and then the means of the remaining elements in the four regions can be counted. At this time, the means of the four remaining elements can be obtained, and the minimum value is selected as the noise level value of the residual matrix. Usually, the above threshold coefficient is set to 3, and the noise level value of the selected residual matrix is ​​multiplied by the threshold coefficient 3, which is the threshold value. After obtaining the threshold value, the 0-1 detection step can be continued. Moreover, since the threshold value is calculated based on the residual matrix, and the residual matrix is ​​obtained from the observation data matrix, the threshold value is targeted to the observation data matrix.

[0055] In actual use, every time an observation data matrix is ​​obtained, a corresponding threshold value can be calculated when executing the pedestrian information detection method of the embodiment of the present disclosure, so as to avoid the inaccurate calculation phenomenon caused by using the same threshold value. That is, the above-mentioned implementation method of calculating the threshold value based on the remaining elements also helps to improve the accuracy of detection.

[0056] Furthermore, when 0-1 detection is performed based on the above threshold value in the above step S210, the following marking operation can be performed for each remaining element included in the remaining matrix: determine whether the remaining element is greater than the threshold value; if so, mark the position of the remaining element in the remaining matrix as 1; if not, mark the position of the remaining element in the remaining matrix as 0; generate a marking matrix corresponding to the remaining matrix according to the result of the marking operation; and then count the pedestrian information on the intelligent ground based on the marking matrix.

[0057] Furthermore, when counting pedestrian information based on the marking matrix, the number of areas connected by the elements marked as 1 in the marking matrix can be counted, and the number of areas can be determined as the number of pedestrians on the current smart ground; and / or, the relative positions of the areas connected by the elements marked as 1 in the marking matrix can be counted, and the relative positions can be determined as the position information of the pedestrians on the current smart ground.

[0058] That is, when determining pedestrian information, it is possible to determine the number of pedestrians on the smart ground, or the positions of pedestrians on the smart ground, or to determine both the number of pedestrians and the positions of pedestrians on the smart ground at the same time. The specific pedestrian information can be set according to the actual situation, and the embodiments of the present disclosure do not limit this.

[0059] For ease of understanding, the dot matrix sensor network composed of ground sensors is taken as an example of a 24*35 dot matrix, where 24 is the number of rows and 35 is the number of columns. At this time, the obtained observation data matrix is ​​also a 24*35 data matrix. Based on the 24*35 observation data matrix, the process of pedestrian information detection can include the following steps:

[0060] (1) When selecting an unmanned period, record the intelligent ground detection signal. Record 10,000 frames of data matrix with ground clutter, that is, obtain a 10,000-frame detection signal matrix, then calculate the mean of the elements at the same position in the detection signal matrix of each frame to obtain the mean signal at that position, traverse each element in the detection signal matrix, calculate the mean signal at that position, and generate the clutter scene matrix B according to the mean signal corresponding to each position.

[0061] For the sake of explanation, it is assumed that the clutter signal of the smart ground in this scenario is generated by a stationary table. During the unmanned period, the table can stimulate the ground sensor to generate clutter signals. Usually, for the sake of demonstration of clutter signals, the matrix generated by the ground sensor data can be converted into a grayscale image, that is, the dot matrix data is converted into image data. The specific conversion process is not limited in the embodiments of the present disclosure. Figure 3 A schematic diagram of a clutter scene matrix is ​​shown, which illustrates the clutter signal. Figure 3As shown, it is displayed in the form of a grayscale image, and Figure 3 We can see a more obvious signal, such as Figure 3 The square box shows the clutter signal during unmanned periods.

[0062] (2) When there are pedestrians, obtain a frame of observation data matrix A of the smart ground, such as Figure 4 A schematic diagram of an observation data matrix is ​​shown, including Figure 3 clutter signals, and pedestrian signals.

[0063] (3) Subtract the element value of the corresponding position in the clutter scene matrix B from each element value in the observation data matrix A to obtain the remaining elements. The remaining matrix C corresponding to the observation data matrix is ​​generated based on the remaining elements. The remaining matrix C can be expressed as Figure 5 ,Right now, Figure 5 In the residual matrix schematic diagram shown, the residual matrix C represents the matrix from which the clutter signal is eliminated.

[0064] (4) Use the residual matrix C to perform target detection and obtain the pedestrian detection result after removing clutter. Figure 6 A schematic diagram of pedestrian information detection results is shown. It can be seen that fixed clutter targets are eliminated, while pedestrian targets are well detected.

[0065] Furthermore, the results of the above-mentioned pedestrian information detection can be used to count the flow of people within a limited range, such as the size of the flow of people within a certain time period, and the distribution of pedestrians within a limited range, etc. The application of specific detection results can also be set according to actual usage, and the embodiments of the present disclosure do not limit this.

[0066] Further, based on the above embodiments, the present disclosure also provides a pedestrian information detection device, such as Figure 7 The schematic diagram of the structure of a pedestrian information detection device shown in FIG. 1 includes the following structures:

[0067] The acquisition module 70 is used to acquire the observation data matrix of the ground sensor; wherein the ground sensor is arranged on the intelligent ground according to a preset dot matrix pattern, and is used to generate an excitation signal when stimulated; the observation data matrix is ​​generated by multiple ground sensors according to the excitation signal at the same frame time;

[0068] A calculation module 72, configured to calculate a residual matrix corresponding to the observation data matrix according to a pre-stored clutter scene matrix, wherein the clutter scene matrix is ​​a data matrix generated according to an excitation signal of a ground sensor during an unmanned period;

[0069] The detection module 74 is used to perform target detection on the remaining matrix to obtain pedestrian information on the intelligent ground.

[0070] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0071] Furthermore, the calculation module 72 is used for:

[0072] Subtract the element value at the corresponding position in the clutter scene matrix from each element value in the observation data matrix to obtain the remaining elements; and generate the remaining matrix corresponding to the observation data matrix according to the remaining elements.

[0073] Furthermore, the detection module 74 is used to:

[0074] A threshold value corresponding to the residual matrix is ​​calculated according to a plurality of residual elements included in the residual matrix; and a 0-1 detection is performed on the residual matrix based on the threshold value to obtain pedestrian information on the intelligent ground.

[0075] Furthermore, the detection module 74 is also used for:

[0076] A preset number of independent regions are randomly selected in the residual matrix; the independent regions include a plurality of residual elements; the mean of the residual elements included in each independent region is calculated, and the minimum value among the means is selected as the noise level value of the residual matrix; and the noise level value is multiplied by a preset threshold coefficient to obtain a threshold value.

[0077] Furthermore, the detection module 74 is also used for:

[0078] For each remaining element included in the remaining matrix, the following marking operation is performed: determine whether the remaining element is greater than a threshold value; if so, mark the position of the remaining element in the remaining matrix as 1; if not, mark the position of the remaining element in the remaining matrix as 0; generate a marking matrix corresponding to the remaining matrix based on the result of the marking operation; and count pedestrian information on the intelligent ground based on the marking matrix.

[0079] Furthermore, the detection module 74 is also used for:

[0080] Count the number of areas connected by elements marked as 1 in the marking matrix, and determine the number as the number of pedestrians on the current smart ground; and / or count the relative positions of areas connected by elements marked as 1 in the marking matrix in the marking matrix, and determine the relative positions as the location information of pedestrians on the current smart ground.

[0081] Furthermore, the above device is also used for:

[0082] Acquire the excitation signals of multiple frames of ground sensors during unmanned periods, and generate a detection signal matrix of the ground sensor in each frame according to the excitation signals, wherein each element in the detection signal matrix corresponds to an excitation signal of a ground sensor; calculate the mean of the elements at the same position in the detection signal matrix of each frame to obtain the mean signal at that position; traverse each element in the detection signal matrix, calculate the mean signal at that position, and generate a clutter scene matrix according to the mean signal corresponding to each position.

[0083] The pedestrian information detection device provided by the embodiment of the present disclosure can obtain the observation data matrix of the ground sensor, and calculate the residual matrix corresponding to the observation data matrix according to the pre-stored clutter scene matrix, and then perform target detection on the residual matrix to obtain pedestrian information on the intelligent ground. Since the above-mentioned clutter scene matrix is ​​a data matrix generated according to the excitation signal of the ground sensor during the unmanned period, when the residual matrix is ​​calculated according to the clutter scene matrix, the clutter signal in the observation data matrix can be eliminated, and then the residual matrix including only the pedestrian signal is obtained, avoiding the influence of clutter on the pedestrian signal, and at the same time, reducing the amount of calculation, which helps to improve the accuracy of detection.

[0084] The pedestrian information detection device provided in the embodiment of the present disclosure has the same technical features as the pedestrian information detection method provided in the above embodiment, so it can also solve the same technical problems and achieve the same technical effects.

[0085] Furthermore, the embodiment of the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above Figure 1 or Figure 2 The method shown.

[0086] The present disclosure also provides a computer-readable storage medium on which a computer program is stored. The computer program is executed by a processor. Figure 1 or Figure 2 The method shown.

[0087] The computer program product of the pedestrian information detection method, device and electronic device provided in the embodiments of the present disclosure includes a computer-readable storage medium storing program codes. The instructions included in the program codes can be used to execute the methods in the previous method embodiments. The specific implementation can be found in the method embodiments and will not be repeated here.

[0088] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0089] Further, the flowcharts and block diagrams in the accompanying drawings of the embodiments of the present disclosure show the possible architecture, functions and operations of the systems, methods and computer program products according to the multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0090] Further, in the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0091] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0092] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0093] In addition, in the description of the embodiments of the present disclosure, unless otherwise clearly specified and limited, the terms "connected", "installed", and "connected" should be understood in a broad sense, for example, it can be a detachable connection, a fixed connection, or an integral connection; it can be an electrical connection or a mechanical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present disclosure can be understood according to specific circumstances.

[0094] In the description of the present disclosure, it should be noted that the terms "up", "down", "center", "left", "right", "vertical", "horizontal", "inside", "outside", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the referred elements or devices must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present disclosure.

[0095] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0096] Finally, it should be noted that the above embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The protection scope of the present disclosure is not limited thereto. Although the present disclosure is described in detail with reference to the above embodiments, those skilled in the art should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above embodiments within the technical scope disclosed in the present disclosure, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A pedestrian information detection method, characterized in that: include: Acquire an observation data matrix of a ground sensor; wherein the ground sensor is arranged on the smart ground according to a preset dot matrix pattern, and the ground sensor is a pressure sensor or an infrared sensor, which is used to generate an excitation signal when stimulated; the observation data matrix is ​​generated by a plurality of the ground sensors according to the excitation signal at the same frame time; Calculating a residual matrix corresponding to the observation data matrix according to a pre-stored clutter scene matrix, wherein the clutter scene matrix is ​​a data matrix generated according to an excitation signal of the ground sensor during an unmanned period; Performing target detection on the remaining matrix to obtain pedestrian information on the smart ground; The step of calculating the residual matrix corresponding to the observation data matrix according to the pre-stored clutter scene matrix includes: Subtract the element value at the corresponding position in the clutter scene matrix from each element value in the observation data matrix to obtain the remaining element; A residual matrix corresponding to the observation data matrix is ​​generated according to the residual elements.

2. The method according to claim 1, characterized in that: The step of performing target detection on the remaining matrix to obtain pedestrian information on the smart ground comprises: Calculating a threshold value corresponding to the residual matrix according to the plurality of residual elements included in the residual matrix; The remaining matrix is ​​subjected to 0-1 detection based on the threshold value to obtain pedestrian information on the smart ground.

3. The method according to claim 2, characterized in that The step of calculating the threshold value corresponding to the residual matrix according to the plurality of residual elements included in the residual matrix comprises: Randomly selecting a preset number of independent regions in the remaining matrix; the independent regions include a plurality of the remaining elements; Calculate the mean of the remaining elements included in each of the independent regions, and select the minimum value of the mean as the noise level value of the remaining matrix; The noise level value is multiplied by a preset threshold coefficient to obtain the threshold value.

4. The method according to claim 2, characterized in that: The step of performing 0-1 detection on the remaining matrix based on the threshold value to obtain pedestrian information on the smart ground comprises: For each of the remaining elements included in the remaining matrix, the following marking operation is performed: determining whether the remaining element is greater than the threshold value; if so, marking the position of the remaining element in the remaining matrix as 1; if not, marking the position of the remaining element in the remaining matrix as 0; Generate a marking matrix corresponding to the remaining matrix according to the result of the marking operation; Pedestrian information on the smart ground is counted based on the marking matrix.

5. The method according to claim 4, characterized in that The step of counting pedestrian information on the smart ground based on the marking matrix includes: Counting the number of areas connected by elements marked as 1 in the marking matrix, and determining the number as the number of pedestrians currently on the smart floor; and / or, The relative positions of the areas connected by the elements marked as 1 in the marking matrix are counted, and the relative positions are determined as the current position information of the pedestrian on the intelligent ground.

6. The method according to claim 1, characterized in that The method further comprises: Acquire multiple frames of excitation signals of the ground sensor in an unmanned period, and generate a detection signal matrix of the ground sensor in each frame according to the excitation signals, wherein each element in the detection signal matrix corresponds to an excitation signal of the ground sensor; Calculating the mean of the elements at the same position in the detection signal matrix of each frame to obtain the mean signal at the position; Each element in the detection signal matrix is ​​traversed to calculate the mean signal at the position, and the clutter scene matrix is ​​generated according to the mean signal corresponding to each position.

7. A pedestrian information detection device, characterized in that: include: An acquisition module is used to acquire an observation data matrix of a ground sensor; wherein the ground sensor is arranged on the intelligent ground according to a preset dot matrix pattern, and the ground sensor is a pressure sensor or an infrared sensor, which is used to generate an excitation signal when stimulated; the observation data matrix is ​​generated by a plurality of the ground sensors according to the excitation signal at the same frame time; A calculation module, used for calculating a residual matrix corresponding to the observation data matrix according to a pre-stored clutter scene matrix, wherein the clutter scene matrix is ​​a data matrix generated according to an excitation signal of the ground sensor during an unmanned period; A detection module, used for performing target detection on the remaining matrix to obtain pedestrian information on the smart ground; The step of calculating the residual matrix corresponding to the observation data matrix according to the pre-stored clutter scene matrix includes: Subtract the element value at the corresponding position in the clutter scene matrix from each element value in the observation data matrix to obtain the remaining element; A residual matrix corresponding to the observation data matrix is ​​generated according to the residual elements.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is executed.

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