WO2020048156A1 - Procédé et appareil de comptage de flux de véhicules, dispositif de comptage, et support de stockage lisible par ordinateur - Google Patents

Procédé et appareil de comptage de flux de véhicules, dispositif de comptage, et support de stockage lisible par ordinateur Download PDF

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Publication number
WO2020048156A1
WO2020048156A1 PCT/CN2019/087229 CN2019087229W WO2020048156A1 WO 2020048156 A1 WO2020048156 A1 WO 2020048156A1 CN 2019087229 W CN2019087229 W CN 2019087229W WO 2020048156 A1 WO2020048156 A1 WO 2020048156A1
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WIPO (PCT)
Prior art keywords
vehicle
video
reference line
video stream
distance
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PCT/CN2019/087229
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English (en)
Chinese (zh)
Inventor
李涛
林伟彬
李健
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华为技术有限公司
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Publication of WO2020048156A1 publication Critical patent/WO2020048156A1/fr

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing

Definitions

  • This application relates to the field of video, and in particular, to a method and device for counting vehicle traffic, a computing device, and a computer-readable storage medium.
  • Vehicles have become a common means of transportation for people to travel. With the popularization of vehicles, roads (such as urban traffic) are often congested, so traffic flow needs to be monitored.
  • the current monitoring method is to use radar signals to monitor passing vehicles, or to use gravity sensors to monitor passing vehicles.
  • the present application provides a method, a device, and a computing device for counting vehicle traffic, which can implement monitoring of vehicle traffic through video streaming.
  • the present application provides a method for counting vehicle traffic.
  • the computing device obtains a video stream that monitors vehicle traffic; for example, the video stream may be a video stream generated by a shooting device that monitors vehicle traffic on a road, and the computing device obtains the video stream from the shooting device.
  • the video stream includes a plurality of video frames.
  • the computing device identifies a vehicle in each video frame from the video stream.
  • the computing device calculates the vehicle flow monitored by the video stream according to the time sequence and the direction of the vehicle flow according to the vehicle in each video frame in the video stream.
  • the present application can monitor the traffic flow on the road by means of video streaming.
  • the computing device may calculate the vehicle flow in the following manner.
  • the computing device sets a reference line at the same position in each video frame in the video stream, the reference line being perpendicular to the direction of the vehicle flow. In this way, the computing device can count vehicles passing the reference line.
  • the computing device identifies the number of vehicles passing the reference line from the video stream according to the time sequence and the direction of the vehicle flow.
  • the number of vehicles passing the reference line is the traffic volume.
  • the computing device may identify the number of vehicles passing the reference line from the video stream in the following manner.
  • the computing device determines a target vehicle in each video frame, and the target vehicle is a vehicle that is closest to the reference line in the video frame in the direction of the traffic flow.
  • the computing device calculates the distance between the target vehicle in the video frame and the reference line, and uses the calculated distance as the target distance in the video frame.
  • the computing device can calculate the target distance in each video frame in the video stream.
  • the computing device identifies each vehicle passing the reference line in chronological order, based on a strategy and a target distance in each of the video frames in the video stream.
  • the strategy is: identifying the currently passing vehicle when the target distance in the first video frame is less than the target distance in the second video frame, and the first video frame and the second video frame are in the video stream Two video frames next to each other in chronological order.
  • the present application can recognize the number of vehicles passing the reference line through the event that the target distance of adjacent video frames in the video stream becomes larger, and simultaneously identify the number of vehicles passing the reference line.
  • vehicles that pass through the reference line each time can be identified; in this way, vehicles that pass through the reference line all times, that is, traffic flow can be calculated.
  • the computing device calculates a distance from a head of a target vehicle in the video frame to a reference line, and the calculated distance is the distance in the video frame. Target distance.
  • the computing device calculates a distance from a tail of a target vehicle in the video frame to a reference line, and the calculated distance is in the video frame. Target distance.
  • the computing device calculates a distance from a reference point on a vehicle body of a target vehicle in the video frame to a reference line, and the calculated distance is The target distance in the video frame.
  • the present application provides a device for counting vehicle traffic, including a plurality of functional units.
  • the device executes the steps in the first aspect or the method for counting traffic flow provided by any possible design of the first aspect through the multiple functional units.
  • the present application provides a computing device including a processor and a memory.
  • the memory stores computer instructions; the processor executes the computer instructions stored in the memory, so that the computing device executes steps in the first aspect or any possible design provided by the first aspect of the method for counting vehicle traffic.
  • the computer instructions stored in the memory are used to implement a functional unit in any one of the devices for counting vehicle traffic provided by the second aspect.
  • the computing device executes the steps in the method for counting vehicle traffic through the functional unit.
  • a computer-readable storage medium stores computer instructions.
  • the processor of the computing device executes the computer instructions
  • the computing device executes the first aspect or any possibility of the first aspect. Steps in designing a provided method for counting vehicle traffic.
  • the computer instructions stored in the computer-readable storage medium are used to implement a functional unit in any one of the devices for counting vehicle traffic provided by the second aspect.
  • the computing device executes the steps in the method for counting vehicle traffic through the functional unit.
  • a computer program product includes computer instructions stored in a computer-readable storage medium.
  • the processor of the computing device may read and execute the computer instructions from the computer-readable storage medium, so that the computing device executes the steps in the method of counting vehicle traffic provided by the first aspect or any possible design provided by the first aspect.
  • the computer instructions in the computer program product are used to implement a functional unit in any one of the devices for counting vehicle traffic provided by the second aspect.
  • the computing device executes the steps in the method for counting vehicle traffic through the functional unit.
  • a system for counting vehicle traffic includes a computing device and a photographing device in the first aspect or any possible design of the first aspect.
  • the computing device executes the steps in the first aspect or any possible design method provided by the first aspect of the method for counting vehicle traffic, for example, the computing device deploys the device for counting vehicle traffic provided by the second aspect, and the computing device passes the device in the device.
  • FIG. 1 is a schematic diagram of traffic flow
  • FIG. 2 is a schematic diagram of a scenario to which the method provided by this application is applicable;
  • FIG. 3 is a schematic flowchart of a method for counting traffic flow provided by the present application.
  • FIG. 4A and FIG. 4B are respectively a schematic diagram for identifying the passage of a vehicle provided by the present application.
  • FIG. 5 is a schematic diagram of a logical structure of a device 50 for counting vehicle traffic provided by the present application
  • FIG. 6 is a schematic diagram of a hardware structure of a computing device 12 provided in this application.
  • Vehicle means the vehicle that moves the body by turning the wheels.
  • the vehicle may be a non-motor vehicle or a motor vehicle.
  • Traffic flow direction the direction in which multiple vehicles move on the road in the same direction. Taking Figure 1 as an example, three vehicles (A, B, C) are driving in the lane. These three vehicles are driving in the same direction, and this direction is the direction of traffic flow.
  • Traffic refers to vehicles that pass through the same reference line on the road in the same direction in unit time.
  • Figure 1 illustrates the reference line.
  • Vehicles (A, B) have not reached the reference line, and vehicle C is passing through the reference line.
  • the reference line may be a straight line or a line composed of a plurality of spaced points.
  • the reference line may be a straight line or other types of lines.
  • the reference line is perpendicular to the direction of the traffic flow.
  • a method for calculating the traffic flow When the number of vehicles passing the reference line within a preset time period is M, the traffic flow is a ratio of M to the preset time period, and M is a positive integer.
  • the system includes a photographing device 21 and a computing device 22. It can be understood that, in another embodiment, the system may further include other processing devices, such as a network forwarding device, a video processing device, and the like.
  • the photographing device 11 is configured to acquire a traffic flow on a monitored road and photograph a vehicle passing through a fixed road segment.
  • the photographing device 11 forms a video stream based on the photos obtained by continuous photographing, and the video stream includes multiple video frames, that is, each frame in the video stream is a video frame.
  • This application does not limit the manner of forming a video stream based on multiple photos; for example, one photo obtained from each photo may be a video frame, and multiple photos obtained from the photo are combined into a video stream in chronological order; for example, A plurality of photos obtained by taking pictures are processed to form a video stream.
  • One photo corresponds to one video frame, but the characteristics of the vehicle in the picture are retained in the video frame.
  • the photographing device 11 sends the generated video stream to a computing device 12 in the system.
  • the computing device 12 may use the method provided in the present application to count the vehicle traffic.
  • This application provides an embodiment of a method for counting vehicle traffic.
  • the computing device 12 in the embodiment shown in FIG. 2 described above can be used to count vehicle traffic.
  • the method includes steps S31, S32, and S33, as shown in FIG.
  • step S31 the computing device 12 obtains a video stream from the photographing device 11.
  • the video stream is a video stream obtained by the shooting device 11 monitoring the traffic flow of a preset road segment, and the video stream includes a plurality of video frames.
  • the computing device 12 may request a video stream from the shooting device 11, and the shooting device 11 sends the video stream to the computing device 12.
  • the shooting device 11 may actively send the video stream to the computing device 12, for example, periodically send the video stream to the computing device.
  • the computing device 12 receives the video stream sent by the photographing device 11 and thus completes the acquisition of the video stream.
  • step S32 the computing device 12 identifies a vehicle in each video frame from the video stream.
  • the video stream includes a plurality of video frames, and the computing device 12 makes a vehicle identification for each video frame in the video stream.
  • the computing device 12 deploys a Convolutional Neural Network (CNN) algorithm for identifying vehicles.
  • CNN Convolutional Neural Network
  • the computing device 12 uses the CNN algorithm to identify vehicles from the video frame, for example, to identify vehicles closest to the reference line, or to identify all vehicles.
  • the computing device 12 deploys a candidate region (RP) algorithm for identifying a vehicle.
  • the computing device 12 uses the RP algorithm to identify vehicles from the video frame, for example, to identify the vehicle closest to the above reference line, or to identify all vehicles.
  • step S33 the computing device 12 calculates the traffic flow monitored by the video stream according to the time sequence and the direction of the traffic flow, based on the vehicles in each of the video frames identified from the video stream.
  • the computing device 12 can calculate the preset according to the chronological order and the direction of the traffic flow. Traffic on road segments. The following examples provide several statistical methods.
  • the computing device 12 can count the number of vehicles entering the preset road segment according to the time sequence and the direction of the traffic flow.
  • the computing device 12 may calculate the traffic volume of the preset road segment monitored by the video stream according to the counted number and the time period monitored by the video stream.
  • the range of scenes ie, preset road segments
  • the range of scenes that can be monitored by a video stream is limited.
  • it can be identified from the pair of adjacent video frames of the video stream whether a new vehicle has entered the preset road segment; if a new vehicle has entered , Then the number of newly driven vehicles is identified.
  • the newly entered vehicles can be identified from the video stream, and the total number of newly entered vehicles can be counted each time. Therefore, the traffic volume of the preset road segment monitored by the video stream can be calculated according to the sum of statistics and the time period monitored by the video stream.
  • the computing device 12 may count the number of vehicles driving out of the preset road segment according to the time sequence and the direction of the traffic flow.
  • the computing device 12 may calculate the traffic volume of the preset road segment monitored by the video stream according to the counted number and the time period monitored by the video stream.
  • the range of scenes (ie, preset road segments) that can be monitored by a video stream is limited.
  • it can be identified from the pair of adjacent video frames of the video stream whether a new vehicle is driving out of the preset road segment; if a new vehicle is driving out , The number of newly driven vehicles is identified.
  • the traffic volume of the preset road segment monitored by the video stream can be calculated according to the sum of statistics and the time period monitored by the video stream.
  • the computing device 12 may set a reference line for each video frame in the video stream at the same position in each video frame, as shown in FIG. 1, the reference line and the vehicle flow Direction is vertical.
  • this method is not limited to the specific position of the reference line in the video frame. For example, it can be set at the entrance or exit of the traffic direction in the video frame, and can also be set at any other position in the video frame. position.
  • the computing device 12 After setting the reference line, the computing device 12 identifies vehicles passing the reference line from the video stream in chronological order and the direction of the traffic flow. The computing device 12 counts the number of vehicles passing the reference line, and may calculate the traffic volume of the preset road segment monitored by the video stream according to the counted number and the time period monitored by the video stream.
  • An example is optionally provided to identify a vehicle passing the reference line from the video stream.
  • the computing device 12 determines a target vehicle in each video frame in the video stream, and the target vehicle is a vehicle that is closest to the reference line in the direction of the flow in the video frame. In the video frame, the distance between the target vehicle of the video frame and the reference line is calculated, and the calculated distance is used as the target distance in the video frame.
  • the computing device 12 identifies each vehicle passing the reference line in chronological order according to a policy and a target distance in each of the video frames in the video stream.
  • the strategy is: the first video frame and the second video frame are two video frames adjacent to each other in time sequence in the video stream; the target distance in the first video frame is smaller than the target in the second video frame
  • the number of currently passing vehicles can be identified.
  • the number of passing vehicles can be one or more. If multiple vehicles pass at the same time, the number of vehicles passing at the same time is identified. If only one vehicle passes, the number of vehicles identified as passing is one.
  • step S32 Since the vehicle in each video frame has been identified in step S32, that is, the position of the vehicle in the video frame has been identified, so when a vehicle is passed through the reference line according to the strategy, the currently passing vehicle and the identification can be further identified. The number of vehicles currently passing.
  • An example is optionally provided to identify a vehicle passing the reference line from the video stream.
  • the computing device 12 calculates the distance between each vehicle and the reference line in each video frame in the video stream, and selects the shortest distance from the calculated distance between each vehicle and the reference line. Distance, using the selected shortest distance as the target distance in the video frame, and the vehicle corresponding to the shortest distance as the target vehicle in the video frame. In the same video frame, if multiple vehicles have the target distance from the reference line, the multiple vehicles simultaneously serve as multiple target vehicles, that is, each of the multiple vehicles is the target vehicle; if only If a vehicle has the target distance from the reference line, the vehicle is regarded as the target vehicle.
  • the computing device 12 identifies each vehicle passing the reference line in chronological order according to a policy and a target distance in each of the video frames in the video stream.
  • the computing device 12 can identify all vehicles passing the reference line in the video stream through the strategy. According to the number of all vehicles passing the reference line, the traffic volume of the preset road segment monitored by the video stream can be calculated.
  • the strategy further includes: identifying that no vehicle passes when the target distance in the first video frame is greater than or equal to the target distance in the second video frame, the first video frame and the second video frame
  • the video frames are two video frames adjacent to each other in the video stream in chronological order. In this way, the computing device 12 can accurately identify whether a vehicle passes the reference line based on the target distance in each of the video frames in the video stream in chronological order through the strategy.
  • the I frame, the J frame, and the K frame are three video frames in the video stream arranged in time sequence.
  • the head of the vehicle C is closest to the reference line compared to the vehicle A and the vehicle B, and the distance between the head of the vehicle C and the reference line is 10 meters (meter, m).
  • the head of the vehicle C is closest to the reference line compared to the vehicle A and the vehicle B, and the distance between the head of the vehicle C and the reference line is 5 meters.
  • the head of vehicle C has passed the reference line, so the distance between vehicle C and the reference line is no longer considered, and only vehicle A and vehicle B are compared; at this time, compared with vehicle A, vehicle B
  • vehicle B The front of the vehicle is closest to the reference line, and the distance between the front of vehicle B and the reference line is 15 meters. Because the distance between vehicle B and the reference line (15 meters) in frame K is greater than the distance between vehicle C and the reference line (5 meters) in frame J, it is recognized that a vehicle has passed, and the vehicle that has passed is identified as vehicle C , That is, the number of passing vehicles is one.
  • the I frame, the J frame, and the K frame are three video frames in the video stream arranged in time sequence.
  • the heads of vehicles B and C are closest to the reference line compared to vehicle A.
  • the distance between the head of vehicle B and the reference line is 10 meters.
  • the distance is 10 meters.
  • the heads of vehicles B and C are closest to the reference line compared to vehicle A.
  • the distance between the head of vehicle B and the reference line is 5 meters, and the distance between the head of vehicle C and the reference line The distance is 5 meters.
  • the head of vehicle B and the head of vehicle C pass the reference line at the same time according to the direction of the traffic, so the distances between vehicle B and vehicle C from the reference line are no longer considered; at this time, the head of vehicle A is away from the reference line
  • the distance between the front of the vehicle A and the reference line was 10 meters. Since the distance between vehicle A and the reference line (10 meters) in frame K is greater than the distance between vehicle C and the reference line (5 meters) in frame J, it is recognized that a vehicle has passed, and the vehicle that has passed is identified as vehicle B. And vehicle C, that is, the number of passing vehicles is two.
  • the computing device 12 calculates the distance between the head of the vehicle and the reference line, and uses the calculated distance as the distance of the vehicle from the reference line. For example, in each video frame, the distance from the head of the target vehicle to the reference line is calculated, and the calculated distance is the target distance in the video frame.
  • the computing device 12 calculates the distance between the tail of the vehicle and the reference line, and uses the calculated distance as the distance of the vehicle from the reference line.
  • a reference point is selected from each vehicle (may be located at the middle position of the vehicle or any other position), and the computing device 12 calculates the reference point of the vehicle and the The distance of the reference line. The calculated distance is taken as the distance of the vehicle from the reference line.
  • This application provides a device for counting vehicle traffic.
  • the device is deployed on the computing device 12 in the embodiment shown in FIG. 2.
  • the device includes functional units for implementing steps in the method for counting vehicle traffic.
  • the embodiment does not limit how to divide the functional units in the device, and a division of the functional units is provided as an example below, as shown in FIG. 5.
  • the device 50 for counting vehicle traffic shown in FIG. 5 includes:
  • An obtaining unit 51 configured to obtain a video stream of monitored vehicle traffic, where the video stream includes multiple video frames;
  • An identification unit 52 configured to identify a vehicle in each of the video frames from the video stream
  • the calculation unit 53 is configured to calculate, according to the time sequence and the direction of the traffic flow, the traffic volume monitored by the video flow according to the vehicles in each of the video frames identified from the video flow.
  • calculation unit 53 is configured to:
  • the number of vehicles passing the reference line is identified from the video stream in chronological order and the direction of the vehicle flow.
  • calculation unit 53 is configured to:
  • the target distance being a distance between a target vehicle in the video frame and the reference line, and the target vehicle being in the video frame The vehicle closest to the reference line in the direction of the traffic flow;
  • each vehicle passing through the reference line is identified according to a strategy and a target distance in each of the video frames in the video stream, the strategy is: the target distance in the first video frame is less than the first When the target distance in the two video frames is recognized, the currently passing vehicle is identified, and the first video frame and the second video frame are two video frames adjacent to each other in time sequence in the video stream.
  • the calculation unit 53 is configured to calculate a distance from a head of the target vehicle to the reference line in each of the video frames, and the calculated distance is a target distance in the video frame.
  • Each function in the acquisition unit 51, the recognition unit 52, and the calculation unit 53 has corresponding steps in the above method. Therefore, for the implementation details of the functions in the acquisition unit 51, the identification unit 52, and the calculation unit 53, refer to the description of the corresponding steps in the foregoing method.
  • a possible basic hardware architecture of the computing device 12 is provided as an example below, as shown in FIG. 6.
  • the computing device 12 includes a processor 121, a memory 122, a communication interface 123, and a bus 124.
  • the number of processors 121 may be one or more, and FIG. 1 illustrates only one of the processors 121.
  • the processor 121 may be a central processing unit (CPU) or an ARM processor. If the computing device 12 has multiple processors 121, the types of the multiple processors 121 may be different or may be the same. Optionally, the multiple processors 121 of the computing device 12 may also be integrated into a multi-core processor.
  • the memory 122 stores computer instructions; for example, the computer instructions include a chain code; for example, the computer instructions are used to implement each step in the method provided by the present application; for example, the computer instructions are used to implement each of the steps included in the apparatus 50 provided in the present application. A functional unit, or used to implement each step in the method provided in this application.
  • the memory 122 may be any one or any combination of the following storage media: non-volatile memory (NVM) (such as read-only memory (ROM), solid state drives (Solid State Drives, SSD), mechanical hard disks, magnetic disks, and entire arrays of disks), volatile memory (volatile memory).
  • NVM non-volatile memory
  • ROM read-only memory
  • SSD Solid State Drives
  • volatile memory volatile memory
  • the communication interface 123 may be any one or any combination of the following devices: a network interface (such as an Ethernet interface), a wireless network card, and other devices having a network access function.
  • the communication interface 123 is used for data communication between the computing device 12 and other devices (for example, a computing device).
  • FIG. 6 shows the bus 124 with a thick line.
  • the processor 121, the memory 122, and the communication interface 123 are connected through a bus 124.
  • the processor 121 can access the memory 122 through the bus 124 and use the communication interface 123 to perform data interaction with other devices (for example, computing devices) through the bus 124.
  • the computing device 12 executes the computer instructions in the memory 122 to implement the method for counting vehicle traffic provided in the present application on the computing device 12 or implement the device 50 provided in the present application on the computing device 12.
  • the computing device 12 is a server in a public cloud, a private cloud, or a hybrid cloud. After the resources of the computing device 12 are virtualized, a device is deployed on the virtualized resources. This device is used to implement the method for counting vehicle traffic provided in this application, or this device is the device 50 provided in this application.
  • the present application provides a computer-readable storage medium.
  • the computer-readable storage medium stores computer instructions.
  • the processor 121 of the computing device 12 executes the computer instructions, the computing device 12 executes the statistics of vehicle traffic provided by the application. Steps in the method.
  • the application provides a computer-readable storage medium.
  • the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the device 50.
  • the application provides a computer program product including computer instructions, the computer instructions being stored in a computer-readable storage medium.
  • the processor of the computing device may read and execute the computer instructions from the computer-readable storage medium, so that the computing device executes the steps of the method for counting vehicle traffic provided by the present application.
  • the application provides a computer program product.
  • the computer program product includes computer instructions for implementing the device 50.

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  • General Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
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Abstract

La présente invention concerne un procédé et un appareil de comptage d'un flux de véhicules, et un dispositif de comptage (12). Le procédé comprend les étapes suivantes : le dispositif informatique (12) obtient un flux vidéo surveillant le flux de véhicules (S31), le flux vidéo comprenant de multiples trames vidéo ; le dispositif informatique (12) identifie des véhicules dans chaque trame vidéo à partir du flux vidéo (S32) ; le dispositif informatique (12) calcule le flux de véhicules surveillé au moyen du flux vidéo selon les véhicules, qui sont identifiés à partir du flux vidéo, dans chaque trame vidéo sur la base d'un ordre chronologique et d'une direction de circulation des véhicules. Selon le procédé, le flux de véhicules sur une route peut être surveillé au moyen du flux vidéo (S33).
PCT/CN2019/087229 2018-09-05 2019-05-16 Procédé et appareil de comptage de flux de véhicules, dispositif de comptage, et support de stockage lisible par ordinateur WO2020048156A1 (fr)

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CN111046820A (zh) * 2019-12-17 2020-04-21 上海船舶研究设计院（中国船舶工业集团公司第六0四研究院） 汽车滚装船中车辆的统计方法、装置及智能终端
CN111369795B (zh) * 2020-03-09 2022-11-08 深圳大学 一种车流量统计方法、装置、设备及存储介质
CN112950961B (zh) * 2021-01-27 2022-07-08 苏州智芯控联信息科技有限公司 车流量统计方法、装置、设备和存储介质

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