486 results about "Pedestrian flow" patented technology

The invention discloses an improved weighting region matching high-altitude video pedestrian recognizing method (KS-WRM (KS-weighting matching region)). The improvement is reflected as follows: 1) confirming a candidate region by utilizing Kalman filtering; 2) fixing a camera or not by adopting different pedestrian detecting strategies; 3) proposing a pedestrian detecting method of an HLS (hue, lightness and saturation) model with multi-characteristic fusion; and 4) dividing pedestrians based on CA obvious region detection of context sensing. According to the invention, pedestrians can be recognized accurately under complex occasions of blur details, complex backgrounds, noise influences and the like. And the improved weighting region matching high-altitude video pedestrian recognizing method (KS-WRM) provided by the invention can be used for pedestrian detection and recognition at places with high visitor flow rate, such as remote sensing satellite images, malls, subway stations, railway stations, airports, as well as intelligent traffic control, intelligent vehicle auxiliary driving, pedestrian flow rate statistics and analysis places.

Based on area and color analyses, a cost-effective bi-directional people counter dedicated to the pedestrian flow passing through a gate or a door is proposed. Firstly, the passing people are roughly counted with the area of people projected on an image captured by a zenithal video camera. The moving direction of the pedestrian can be recognized by tracking each people-pattern with an analysis of its HSI histogram. To improve the accuracy of counting, the color vector extracted from the quantized histograms of intensity or hue is introduced to refine the early counting. Besides, the inherent problems of both people touching together and merge / split phenomenon can be overcome.

The invention discloses a crowd density estimation method based on video analysis and a pedestrian volume statistical method based on the video analysis. The crowd density estimation method includes the flowing steps of (1) off-line training: manually counting crowd density data, extracting characteristics and conducting training; and (2) on-line estimating: extracting the characteristics and conducting regression prediction by utilizing trained model parameters. The pedestrian volume statistical method includes the step of setting up a robust relationship between a scene and a line-passing number of people by combing the crowd density and a micro-region pedestrian flow speed before a line is passed. Characteristics such as foregrounds, edges and gray scale co-occurrence matrixes are extracted based on a whole area to conduct crowd density estimation, problems of dense crowds, sheltering and the like can be well solved through mixing of the characteristics, and real-time crowd density estimation is achieved. In addition, on the basis of area crowd density estimation, pedestrian volume estimation is conducted through combination of the pedestrian flow speed based on an optical flow, detection and tracking of a large number of individuals under a complex environment are avoided, and two-way pedestrian volume counting of accurate robust under dense crowds is achieved.

The invention provides a method and a device for tracking crowds and counting pedestrian flow. The method includes acquiring real-time color images and depth images of scenes; preprocessing the images; carrying out difference operation on backgrounds of the depth images to obtain moving foreground depth images; detecting pedestrian head regions in the foreground depth images and dividing the pedestrian head regions from the foreground depth images; judging the head regions and removing non-head regions; matching and tracking pedestrian heads according to joint matching probability functions; creating head state spatial switching relational graphs to count the pedestrian heads. The method and the device have the advantages that the position of each pedestrian can be tracked and recorded by the aid of the method and the device, the speeds and the directions of the pedestrians in walking procedures can be computed, the crowds can be tracked under various conditions, and the pedestrian flow can be counted under the various conditions; the method and the device are free of influence of illumination conditions and illumination change; false alarm due to false objects can be filtered out; the device is stable in performance and high in speed, efficiency and accuracy.

The embodiment of the invention provides a block pedestrian flow prediction method and system based on a space-time diagram convolutional neural network. The method comprises the following steps: acquiring historical movement track data of pedestrian flow in a block; inputting the block pedestrian flow movement track data into a pre-trained block pedestrian flow prediction model to obtain a blockfuture pedestrian flow prediction result output by the block pedestrian flow prediction model, wherein the block pedestrian flow prediction model is obtained by constructing a dynamic space-time diagram, classifying blocks by using interest points and training a three-dimensional diagram convolutional neural network model. According to the embodiment of the invention, the method and system achievethe better pedestrian flow prediction performance through the construction of the dynamic graph representing the spatial correlation and time dynamics, the representation of the functional attributesof different blocks through the interest points, and the simultaneous prediction of pedestrian flow and block functions through the multi-task learning.

The invention, which belongs to the virtual simulation technology field, more particularly relates to an integrated traffic simulation system based on interaction usages of macroscopic, mid-scopic and microscopic traffic simulation platforms. The system comprises a macroscopic traffic simulation module, a mid-scopic traffic simulation module, a microscopic traffic simulation module and a data collection and fusion module. The mid-scopic traffic simulation module is connected with the macroscopic traffic simulation module; the microscopic traffic simulation module is connected with the mid-scopic traffic simulation module; and the data collection and fusion module is respectively connected with the macroscopic traffic simulation module, the mid-scopic traffic simulation module and the microscopic traffic simulation module. According to the invention, on the basis of independent simulation of macroscopic, mid-scopic and microscopic traffic simulation platforms, interaction utilization of all layers of simulation systems and various simulation platform data is realized; traffic operation states of traffic flows and pedestrian flows large-scale activities can be comprehensively simulated; therefore, a technological basis can be provided for formulation of various traffic decision schemes of large-scale activities.

The invention discloses an embedded computer vision escalator pedestrian flow supervision and alarm device, which performs supervision and alarm on the pedestrian flow of an escalator so as to ensure the safety of passengers on the escalator. The technical scheme is that the device comprises the following components: an image acquisition device for taking images at the escalator; an embedded computer vision escalator pedestrian flow supervision and alarm system which comprises a computer vision monitoring module comprising an image acquisition submodule, a storage submodule, an analysis submodule, a comparison engine, an alarm operation module, an alarming apparatus, wherein the image acquisition submodule is used for acquiring the images of the passengers on the escalator; the storage submodule is provided with a visual video storage database inside for storing the acquired videos; the analysis submodule is used for analyzing the acquired images; the comparison engine is used for comparing an analysis value with a preset safety range; the alarm operation module is used for sending alarm signals to the passengers according to the obtained abnormal behavior conclusion; and the alarming apparatus is used for performing caution actions. The escalator pedestrian flow supervision and alarm device is applied in the field of escalator safety supervision devices.

The invention belongs to a pedestrian traffic parameter extraction method based on mobile laser scanning, and belongs to the technical field of microscopic traffic parameter obtaining. The method comprises the steps: collecting surrounding point cloud of a vehicle through a three-dimensional laser scanner installed on the vehicle; obtaining different types of data objects through data segmentation, clustering, and detection; recognizing a pedestrian, and extracting fixed objects on a road; carrying out the matching of fixed ground objects in two data frames; calculating the movement distance of an autonomous vehicle in the two frames; calculating the speed of a vehicle; and finally carrying out the statistics of traffic parameters of a pedestrian flow. The method is specifically characterized in that a VLP-16 small-size laser radar from the Velodyne company is used for collecting the dynamic data of pedestrians on a road and the surroundings, and the cost is low; for the correlation of target data and the extraction of traffic parameters, the method employs a nearest neighbor method with reflection information in order to obtain the accurate matching information in the multiframe data, and solves a problem of target matching well.

Based on area and color analyses, a cost-effective bi-directional people counter dedicated to the pedestrian flow passing through a gate or a door is proposed. Firstly, the passing people are roughly counted with the area of people projected on an image captured by a zenithal video camera. The moving direction of the pedestrian can be recognized by tracking each people-pattern with an analysis of its HSI histogram. To improve the accuracy of counting, the color vector extracted from the quantized histograms of intensity or hue is introduced to refine the early counting. Besides, the inherent problems of both people touching together and merge / split phenomenon can be overcome.

The invention relates to a signal crossing right turn special lane real-time dynamic control method, and is aimed at solving a domestic civic crossing right turn special lane signal control dynamic time determination problem. The method comprises the following steps: (1) predicating arrived right turn motor vehicle, non-motor vehicle and pedestrian flow in present period; (2) calculating a corresponding basic control time when integration cost is minimal; (3) executing a right turn red light signal according to right turn basic control time; (4) dynamically detecting agglomeration degree magnitude in a conflict zone; (5) determining whether prolonging right turn control time is needed or not, and if so, prolonging the right turn control time, otherwise releasing the right turn red light signal if the right turn control time is up. According to the method, practical pass demands of a non-motor vehicle, a pedestrian and a right turn motor vehicle are considered synthetically, delay of each traffic flow passing a crossing is reduced, and conflict minimization of each traffic participant is ensured. While ensuring security of the non-motor vehicle and the pedestrian in a conflict direction, passing efficiency of the right turn motor vehicle is raised.

The invention discloses an all-weather multipath channel pedestrian flow monitoring system based on wireless infrared monitoring. The system comprises a video acquisition terminal, wherein the video acquisition terminal comprises active infrared monitoring cameras and video acquisition modules both installed at the inlets of various pedestrian flow monitoring channels, a codebook background module, an image preprocessing module and a wireless transmission module; and the system further comprises: a central server terminal for receiving acquired pedestrian flow data and performing projection, tracking and counting, wherein the central server terminal comprises a wireless reception module, a new pedestrian flow detection module and a pedestrian flow tracking and counting module. The invention provides an all-weather multipath channel pedestrian flow monitoring system based on wireless infrared monitoring, with excellent self-adaptive ability and outstanding reliability.

The invention provides a visitor flow monitoring method and device, a storage medium and equipment, and is applicable to the technical field of image processing. The method comprises the steps of obtaining a target image of a to-be-monitored pedestrian in a video image; extracting graphic features by using a model trained based on a deep residual network; classifying and positioning an unmanned area, a single person area and a crowd area in the target image by utilizing a crowd detection model; adopting a density regression model to obtain a head distribution density map of the crowd detectionclassification as a crowd area, and calculating the number of people in the crowd area according to the head distribution density map; and counting the number of people in the single person area andthe number of people in the crowd area in the crowd detection classification, and calculating the total number of people in the target image. When people flow is monitored, the number of people in thevideo image is counted based on the deep residual network in combination with crowd detection and density analysis, the number of people in the image can be counted accurately and rapidly, and the method has good robustness.

The invention discloses a multi-target locating and tracking video monitoring method, wherein the locating and tracking video monitoring method is suitable for the moving target where camera field of view is fixed, and there are small dynamic changes at background. Before the system works, firstly the background is trained by Gaussian mixture model, and then the background subtraction method is used to get the foreground image in the next frame of the video, followed by the accurate foreground object area, that is moving target location, is obtained according to the expansion and median filtering; detecting if there is any moving target,if there is moving object, the target location is determined according to the connected domain search, if there is no moving target, then the search turns to the next video frame; the tone space transformation of the target position region image is carried out, and the NTSC space tone diagram I and the HSV space tone diagram H are weighted to get the tone histogram, and the back projection of the image is further obtained, then Meanshift algorithm is used to precisely locate the target position. For the next video frame, the above calculation is repeated. The monitoring method can be used for moving target trajectory analysis, vehicle detection and traffic violations speeding and pedestrian flow detection.

The invention discloses a surveillance video transmission method based on video content analysis, which is characterized by comprising an image acquisition module, an image preprocessing module, a pedestrian flow detection module, a crowd density estimation module, a camera parameter setting and warning module, and a video transmission module. The pedestrian flow detection module is used for detecting and counting pedestrians in a surveillance video image. The crowd density estimation module is used for estimating the density of pedestrian flow in the current video image by use of a crowd density estimation algorithm. The camera parameter setting and warning module is used for sending out a camera parameter modification command and crowd event warning information when pedestrian detection and crowd density detection reach a preset level. According to the invention, the crowd density in a video is estimated by use of a pedestrian detection algorithm and a crowd density estimation algorithm, and the configuration of the camera is modified and corresponding surveillance video transmission is carried out according to the result of estimation. Moreover, 'problematic' videos can be transmitted actively or passively, and warning information can be sent out.

The invention discloses an intersection-based V2P collision avoidance method comprising the steps that firstly, the participants of the game are ensured to be vehicles and pedestrians, and the participants are classified to define their passing strategy sets; secondly, street crossing delay and risk payment of the vehicles and the pedestrians of the intersection are solved and a V2P game model is established; thirdly, traffic reward and punishment payment is added on the basis of delay and risk payment so as to enhance the priority rate of the vehicles; and fourthly, an SEIR virus propagation model is improved, and an IEVRI model is established to analyze the psychology of the traffic participants so as to prove the necessity of introducing traffic rewards and punishments. The pedestrian flow and the vehicle flow in the traffic flow, the distance and the speed of the pedestrians and the vehicles from a decision area to a conflict area and the relative potential of the number of the unit batch of street crossing pedestrians are integrally considered, and the traffic reward and punishment factors are added and the V2P game model is established so that the road traffic safety can be enhanced and the passing efficiency can also be guaranteed.

The invention discloses a road section pedestrian traffic signal control system based on pedestrian crossing clearance time. The road section pedestrian traffic signal control system based on the pedestrian crossing clearance time comprises a pedestrian data acquisition and recording unit, a pedestrian crossing clearance time computing unit and a signal implementation and feedback unit, and is applicable to pedestrian signal timing designs of thick crowd crossing districts and intersections with exclusive pedestrian phases. The road section pedestrian traffic signal control system based on the pedestrian crossing clearance time comprehensively takes time loss and pedestrian crossing traffic capacity decline due to mutual disturbance of stream of people of opposite directions during thick crowd crossing into consideration, overcomes the defects that the pedestrian speed is used as a constant and the pedestrian crossing capacity is unchanged in a traditional pedestrian traffic signal control, so that the timing result is more accurate and practical. Only the pedestrian flow and the pedestrian speed of the pedestrian crossing are needed to be measured and computed, so that the computation is concise.

The invention relates to a pedestrian attribute recognition method and system, computer equipment and a storage medium, and the method comprises the steps: extracting an image frame from a real-time video, inputting the image frame into a trained target detection model, and obtaining a pedestrian image outputted by the trained target detection model; inputting the pedestrian image into a trained pedestrian recognition model, and obtaining a classification result output by the trained pedestrian recognition model according to preset pedestrian attributes, wherein the preset pedestrian attributes comprise a gender attribute and an age attribute; and obtaining the number and proportion of pedestrians with different gender attributes and different age attributes according to the classificationresult. According to the invention, the pedestrian images can be extracted from the real-time video, the data of the pedestrian images are classified and counted to obtain pedestrian flow informationwith different attributes, and the popularity degree and popular groups of the sightseeing scenic spot are indirectly displayed by monitoring the pedestrian flow information with different attributes, and the traffic smoothness and the commercial service range can be reasonably planned.

The invention discloses an urban people flow prediction method based on a Seq2Seq generative adversarial network, and the method comprises the steps: abstracting the urban people flow data at different times into image frames, and representing the people flow through a thermodynamic diagram; Dividing the observation data into training data and labels according to time, and converting the problem into an image problem; The idea of WGAN generative adversarial network is generally adopted, a generator generates pedestrian flow in a certain period of time in the future on the basis of historical data by using a Seq2Seq method, and external factors such as weather are added at the same time; The discriminator uses a Waserstein distance to discriminate true and false data; In the training process, the generator and the discriminator are continuously optimized by combining the generative adversarial loss and back propagation. And finally, when the discriminator cannot discriminate the authenticity, the optimized generator is used for predicting the future urban pedestrian flow. According to the method provided by the invention, the generative adversarial network is used for carrying out urban people flow prediction for the first time, and the problems of fuzzy prediction and slow algorithm convergence are solved in combination with external environment factors.

The invention relates to an intensive pedestrian flow rate real-time detection method based on the color feature. The intensive pedestrian flow rate real-time detection method based on the color feature comprises the following steps: carrying out cluster characteristic analysis on collected hair color picture samples, carrying out preprocessing of distortion correction on videos, carrying out binaryzation according to the color feature, extracting movement foreground according to difference of backgrounds, mixing a binaryzation result and a foreground picture, obtaining an area of heads of pedestrians by analyzing, tracking the pedestrians, recording tracks of the pedestrians, and judging the number of the pedestrians and movement directions according to track information. The intensive pedestrian flow rate real-time detection method based on the color feature can effectively solve the problems of interference of background colors and difficult cutting of foreground of moving targets, is low in computation complexity, can detect the pedestrian flow rate in real time, and is suitable for the field of monitoring of intelligent videos.

The invention discloses a method and device for controlling the time length of traffic lights at a crossroad. The method comprises the steps of acquiring first traffic flow information of a red light lane, acquiring first green light time according to the first traffic flow information, acquiring second traffic flow information of the current green light lane in the last red light time length if the first green light time is greater than preset fixed green light time, and acquiring the equivalent pedestrian flow of the red light lane and the green light lane; judging whether the equivalent pedestrian flow of the red light lane is greater than the equivalent pedestrian flow of the green light lane or not, if the equivalent pedestrian flow of the red light lane is greater than the equivalent pedestrian flow of the green light lane and the difference of the equivalent pedestrian flow of the red light lane and the equivalent pedestrian flow of the green light lane is greater than or equal to a first preset threshold, controlling the next green light time length of the red light lane to be first green light time, and controlling the current green light time length of the green light lane to be unchanged. According to the method and device disclosed by the invention, the traffic light time of the crossroad can be changed flexibly, and pedestrian flow conditions of the crossroad are comprehensively considered, so that more people can be enabled to pass, and the traffic efficiency is increased.

The invention discloses a public area flow tracking method based on video data, which comprises the following steps: obtaining video and video information transmitted from a surveillance camera arranged in a public place, wherein, the video information comprises a surveillance camera number and a shooting time; splitting the video into a series of images in frames; inputting an image into a prediction model trained in advance, and outputting border information, wherein the border information is coordinate information of a border of a human head in the image; comparing the border information ofthe adjacent frames and outputting the coordinates of the position and the trajectory of the human.

The invention discloses an intelligent projection zebra crossing control method and an intelligent projection zebra crossing device, wherein a stop line and the projection of a zebra crossing are controlled according to the lighting states of a pedestrian traffic light and a road traffic light, and the position of the stop line projected by a stop line projector is controlled to be far and near from the center of an intersection according to the number of waiting pedestrians in a pedestrian waiting area on the left side of the advancing direction of a road; the projection of the zebra crossing is divided into a first zebra crossing and a second zebra crossing, the first zebra crossing and the second zebra crossing are respectively indicated by forward arrows with opposite projection directions according to a rule of moving forward to the right, and the width of the first zebra crossing and the width of the second zebra crossing projected by a zebra crossing projector are controlled according to the number of people waiting in pedestrian waiting areas on the left side and the right side of the road in the forward direction. According to the invention, the zebra crossing projection mode and the transverse width are adjusted to shorten the time for the pedestrian flow to go across the road, so that a certain improvement and guidance effect is achieved on the traffic condition.

The invention provides a method and system for detecting pedestrian flow by adopting deformable two-dimensional curves. The method comprises the following steps: adopting a camera, a video line, a video acquisition card and a computer (or digital signal processing (DSP)-based video developing board) to set up a system hardware platform and manufacturing a software interface; firstly placing the camera right above a door (channel) to vertically shoot coming-in and going-out actions of the pedestrians downwards, acquiring the color image of each frame and extracting pedestrian heads according to red, green and blue (R, G, B) values of the acquired current frame image; detecting the edge contour of each pedestrian head on the current frame image by adopting the image segmentation technology and then using the deformable two-dimensional curves to fit the edge contour of each pedestrian head on the current frame image by adopting the curve fitting technology to compute the parameter and central coordinate of each two-dimensional curve; comparing the parameter and distance between centers of each two-dimensional curve on the previous frame image with the parameter and distance between centers of each two-dimensional curve on the current frame image to find out the correspondence; and finally counting the numbers of pedestrians who come in and go out according to the positional relationship between the corresponding two-dimensional curves on the previous frame image and the current frame image and a counting line.

The invention belongs to the crossing field of computer science and traffic engineering, and relates to an indoor pedestrian microscopic simulation method based on a cellular automaton. The method comprises following steps of firstly, carrying out gridding on an indoor pedestrian region, thus obtaining a cellular space corresponding to a cellular automaton model; dividing the cellular space into some convex polygon regions; secondly, judging whether there are pedestrians in each region; stating the temporary destination of each pedestrian; calculating the transfer probability of each pedestrian; simulating movements; observing whether conflicts appear or not; finally, solving the conflicts; and updating the practical position of each pedestrian until the pedestrians arrive at the corresponding destinations. According to the method, the simulation model can correspondingly respond to complex walk environments and not merely distinguish the pedestrians and barriers; moreover, the self-organization phenomena displayed in the regional pedestrian flow indoor evacuation process are simulated; the model simulation effect is effectively improved; and the method is more suitable for simulating and analyzing movement evolution of the pedestrian flow in the indoor complex environments.

The invention discloses a finite-stage machine-based method for detecting an abandoned object. The finite-stage machine-based method comprises the steps of: firstly, establishing a Gaussian mixture background model, respectively establishing a short-time background model and a long-time background model according to different learning rates; secondly, establishing a finite-stage machine for each pixel; with results obtained by detection of two different background models with different updating speeds as inputs and a pixel classifying result output by each finite-stage machine as one binary image, carrying out communicated region analysis on the obtained binary image to obtain the shape and contour of the abandoned object by using a region growth method, and working out a rectangular box enclosing the abandoned object; and finally, timing the obtained rectangular box of the abandoned object, and detecting the abandoned object and alarming when a threshold is reached. According to the finite-stage machine-based method, under the condition that the abandoned object is absorbed by two backgrounds, the abandoned object can be always detected according to the pixel history, less false-alarms and wrong-alarms exist in an actual scene, and a good detection effect can also be obtained in an occasion with intensive pedestrian flow without depending on tracking information.

The invention provides an intelligent lighting control system and method thereof. The system comprises a lighting control module, an infrared detection module, a vehicle flow detection module, a lighting test module, a cloud server module, a data processing module and a lighting terminal module. The method detects pedestrian flow and vehicle flow data transmission in different time periods throughan infrared detection module and a vehicle flow detection module to be stored in a cloud server module, the data processing module reads data from the cloud server module, puts the data into the BP neural network corrected based on the genetic algorithm for training, predicts the person / vehicle flow in each period of the future day, and uploads the obtained person / vehicle flow prediction result to the cloud server module for storage, The lighting control module determines the adjustment of the lighting brightness according to the data prediction result and the lighting intensity detected by the lighting test module, and then controls the lighting terminal module to realize the lighting effect of different modes.

The invention relates to an indoor multi-export pedestrian flow simulation method giving consideration to evacuation guidance. Firstly, gridding processing is conducted on an indoor space, then pedestrian evacuation is initialized, and evacuated pedestrians are arranged in random empty cells in a uniform random distribution mode and are represented by dots different from guiders in color; then, the pedestrians in cells are searched, and the guiding action force exerted to the pedestrians, the acting forces among the pedestrians, visible export attractions and obstacle repulsion forces are parsed, and the four directions towards which the pedestrians go possibly so as to obtain a direction matrix A; finally, the direction matrix is parsed, the pedestrians participate in competition to obtain actual moving directions; the positions of the pedestrians are updated till all the pedestrians reach exports. By the adoption of the method, a pedestrian flow evacuation model based on a cellular automaton can be perfected, the inherent law between the pedestrian flow evacuation effect in a multi-export evacuation guidance scene and a guidance effect is disclosed, and a theoretical support is provided for assessment and optimization of a pedestrian flow evacuation guidance strategy.

The invention discloses a deep learning-based space-time long-short-term urban pedestrian volume prediction method. The method is used for pedestrian volume prediction. According to the method, when the spatial correlation is extracted, and the local convolution is carried out on the correlation of the adjacent regions. The correlation of the remote regions is extracted by using graph convolution,so that the integrity of the spatial correlation is considered while parameters and calculated amount are reduced. According to the method, short-term time dependence and long-term time dependence are captured at the same time, so that a prediction result is more accurate in a time dimension. The regional semantic information distribution is considered. Each type of region of interest (POI) in each region is endowed with a corresponding proportion weight, so that the influence of regional semantics on urban pedestrian flow is utilized more accurately.

The invention discloses a pedestrian flow counting method and a pedestrian flow counting device based on an infrared temperature measurement sensor. According to the pedestrian flow counting method, 6 paths of temperature data on a same vertical line are acquired through an infrared temperature measurement sensing part which is placed on the side of an access, whether a person passes by is judged through analyzing the temperature data, whether the incoming and outgoing of the person end is judged by detecting a time interval when nobody passes, thus the incoming and outgoing information can be judged, control and measurement units transmit the incoming and outgoing information of people to an upper machine in real time, and the upper machine can record the current time, count number of people passing by an entrance and number of people passing by an exit within a time period and obtain the number of people in a place through difference between the two numbers, thereby achieving the automatic, accurate and reliable detection of number of the incoming and outgoing people. The pedestrian flow counting device comprises the infrared temperature measurement sensing part, a temperature acquisition / analysis part, a network device and a computer or an embedded processing device serving as the upper machine. The pedestrian flow counting improves the pedestrian flow counting stabilizability, precision and speed, and can be widely applied to entrances or public places.