[go: up one dir, main page]

WO2020057353A1 - Procédé de suivi d'objet basé sur une balle à grande vitesse, serveur de surveillance, et système de vidéosurveillance - Google Patents

Procédé de suivi d'objet basé sur une balle à grande vitesse, serveur de surveillance, et système de vidéosurveillance Download PDF

Info

Publication number
WO2020057353A1
WO2020057353A1 PCT/CN2019/103776 CN2019103776W WO2020057353A1 WO 2020057353 A1 WO2020057353 A1 WO 2020057353A1 CN 2019103776 W CN2019103776 W CN 2019103776W WO 2020057353 A1 WO2020057353 A1 WO 2020057353A1
Authority
WO
WIPO (PCT)
Prior art keywords
target
target object
speed ball
video
monitoring server
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2019/103776
Other languages
English (en)
Chinese (zh)
Inventor
饶丽光
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Jiuzhou Electric Appliance Co Ltd
Original Assignee
Shenzhen Jiuzhou Electric Appliance Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenzhen Jiuzhou Electric Appliance Co Ltd filed Critical Shenzhen Jiuzhou Electric Appliance Co Ltd
Publication of WO2020057353A1 publication Critical patent/WO2020057353A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
    • G06V20/42—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items of sport video content
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
    • H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources

Definitions

  • the invention relates to the technical field of video surveillance, in particular to a high-speed ball-based object tracking method, a monitoring server, and a video monitoring system.
  • High-speed dome is a kind of intelligent camera.
  • the full name is high-speed intelligent dome camera.
  • High-speed dome has excellent video surveillance capabilities, so it is widely used in various industries.
  • the manager manages the video pictures uploaded by each high-speed ball in the monitoring background. When it is necessary to view the specific picture details of a certain character, the manager manually finds the video picture containing the character and zooms in on the character.
  • the inventor found that the traditional technology has at least the following problems: Because managers often look for the video picture containing the character after the fact, when the video picture is enlarged, although the detailed picture can be viewed, the details The sharpness of the picture is relatively poor and lacks targeted shooting.
  • An object of the embodiments of the present invention is to provide a high-speed ball-based object tracking method, a monitoring server, and a video monitoring system, which can automatically track a target object in real time for targeted shooting.
  • the embodiments of the present invention provide the following technical solutions:
  • an embodiment of the present invention provides a high-speed ball-based object tracking method, which is applied to a monitoring server, and the method includes:
  • the positioning instruction including a target object to be positioned
  • controlling the target high-speed ball to track the target object includes:
  • the target object is a person, and the number of the high-speed ball is at least two, and the high-speed ball can shoot the person from different angles;
  • the controlling the target high-speed ball to track the target object by using the target video frame as a tracking starting point includes:
  • an additional high-speed ball set opposite to the target high-speed ball is detected, and the additional high-speed ball is controlled to take a frontal image of the person, and track the person.
  • the method further includes:
  • the training video data set includes video data of multiple abnormal scenes
  • the preprocessed video data is processed by a convolution algorithm to establish the video detection abnormal model.
  • the receiving a positioning instruction includes:
  • An object corresponding to the image shape data is used as a target object to be positioned.
  • an embodiment of the present invention provides an object tracking device based on a target high-speed ball, which is applied to a monitoring server, and the device includes:
  • a receiving module configured to receive a positioning instruction, where the positioning instruction includes a target object to be positioned
  • a traversal module configured to traverse video data shot by the target high-speed ball according to the positioning instruction to detect the target object
  • a control module is configured to control the target high-speed ball to track the target object, and to reduce or enlarge a video picture including the target object.
  • control module includes:
  • a judging unit configured to judge whether a target video frame including the target object matches a preset video detection abnormal model
  • a control unit configured to control the target high-speed ball to track the target object by using the target video frame as a tracking starting point if matched;
  • a continuing judging unit configured to continue judging whether the target video frame of the next frame containing the target object matches a preset video detection abnormal model if there is no match;
  • an embodiment of the present invention provides a monitoring server, including:
  • At least one processor At least one processor
  • a memory connected in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processing
  • the device can be used to perform the high-speed ball-based object tracking method according to any one of the above.
  • an embodiment of the present invention provides a video monitoring system, including:
  • the monitoring server communicates with each of the high-speed domes.
  • an embodiment of the present invention provides a non-transitory computer-readable storage medium, where the non-transitory computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to cause a monitoring server to execute The high-speed ball-based object tracking method according to any one.
  • an embodiment of the present invention provides a computer program product.
  • the computer program product includes a computer program stored on a non-volatile computer-readable storage medium.
  • the computer program includes program instructions. When the instruction is executed by the monitoring server, the monitoring server is caused to execute the high-speed ball-based object tracking method according to any one of the above.
  • a positioning instruction is received, and the positioning instruction includes a target object to be positioned; second, according to the positioning instruction, the target high-speed ball is traversed Video data to detect the target object; again, control the target high-speed ball to track the target object, and reduce or enlarge the video frame containing the target object. Therefore, on the one hand, it can automatically detect the target object for targeted shooting. On the other hand, it can track the target object automatically, and can reduce or enlarge the video frame containing the target object, so as to provide a high-definition video frame or a larger field of view associated with the target object for the later phase.
  • FIG. 1 is a schematic structural diagram of an object tracking system based on a high-speed ball according to an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of an object tracking method based on a high-speed ball according to an embodiment of the present invention
  • FIG. 3 is a schematic structural diagram of a high-speed ball-based object tracking device according to an embodiment of the present invention.
  • FIG. 4 is a schematic structural diagram of a control module in FIG. 3;
  • FIG. 5 is a schematic structural diagram of a monitoring server according to an embodiment of the present invention.
  • the high-speed ball-based object tracking method according to the embodiment of the present invention can be executed in any suitable type of electronic device with computing capability, such as a monitoring server, a desktop computer, a smart phone, a tablet computer, and other electronic products.
  • the monitoring server here may be a physical server or a logical server virtualized by multiple physical servers.
  • the server may also be a server group composed of multiple servers that can communicate with each other, and each functional module may be separately distributed on each server in the server group.
  • the high-speed ball-based object tracking device may be used as a software system, independently set in the above-mentioned client, or may be one of the functional modules integrated in the processor to execute the high-speed ball-based object of the embodiment of the present invention. Tracking method.
  • FIG. 1 is a schematic structural diagram of a video surveillance system according to an embodiment of the present invention.
  • the video surveillance system 100 includes a plurality of cameras 11, a surveillance server 12, and a mobile terminal 13.
  • the camera 11 is installed in a preset area for collecting video data. It can be understood that the camera 11 is fixedly installed in a preset area according to a preset rule, so as to cover the preset area as much as possible.
  • the camera is arranged on a wall surface, a ground, a roof, or an object surface of the preset area in combination with the specific structure and occlusion of the preset area.
  • Each camera forms a camera group, which is used to monitor a specific surveillance area.
  • Each camera is installed at a different position in a preset area.
  • Each camera is used to capture images of areas at different angles within a preset area.
  • the camera group can capture 360-degree objects in the preset area.
  • each camera in the camera group uploads the collected video data to the same monitoring server.
  • Different monitoring areas correspond to different monitoring servers.
  • the surveillance servers of the two do not share surveillance video with each other.
  • a combination of the camera 11 and a multi-dimensional rotating motor can be used to capture real-time capture of high-definition video frame images in the preset area.
  • a high-definition camera with a waterproof function, a small size, a high resolution, a long life, and a universal communication interface is selected.
  • the camera 11 is a network camera, and the camera 11 has a built-in network coding module.
  • the camera includes a lens, an image sensor, a sound sensor, an A / D converter, a controller, a control interface, a network interface, and so on.
  • the camera may be used to collect video data signals, and the video data signals are analog video signals.
  • the camera is mainly composed of a CMOS light-sensitive component and a peripheral circuit, and is used for converting an optical signal input from the lens into an electrical signal.
  • the network coding module has an embedded chip built therein, the embedded chip is used to convert the video data signals collected by the camera into digital signals, the video data signals are analog video signals, and the embedded chip also The digital signal may be compressed.
  • the embedded chip may be a Hi3516 high-efficiency compression chip.
  • the camera 11 sends the compressed digital signal to the monitoring server 12 through the WIFI network.
  • the monitoring server 12 may send the compressed digital signal to the mobile terminal 13.
  • the camera 11 further includes an infrared sensor, so that the camera 11 has a night vision function. Users on the network can directly view the camera image on the web server with a browser or directly access through the mobile terminal APP.
  • the camera 11 can more easily implement monitoring, especially remote monitoring, with simple construction and maintenance, better support for audio, Better support for alarm linkage, more flexible recording storage, richer product selection, higher-definition video effects and more perfect monitoring and management functions, and the camera can be directly connected to the local area network, which is the data collection and photoelectric signal
  • the conversion end is the data supply end of the entire network.
  • the monitoring server 12 is a device that provides computing services.
  • the composition of the monitoring server includes a processor, a hard disk, a memory, a system bus, and the like. Similar to a general computer architecture, the monitoring server is responsible for providing functions such as mobile terminal APP registration, user management, and device management. At the same time, it is responsible for the video data storage function of the camera, and remembers the IP and port of the mobile terminal and camera through the monitoring server, and transmits the IP and port of the corresponding mobile terminal and camera to each other, so that the camera and mobile end can know The other party's IP and port establish a connection and communication through the IP address and port.
  • the monitoring server obtains the video data of the camera and then analyzes the video data according to the artificial intelligence module. When abnormal video data is detected, it sends an alarm message to notify the mobile terminal.
  • the monitoring server 12 includes a processor, and the processor includes an artificial intelligence module.
  • the artificial intelligence module is responsible for real-time analysis of video data, detects abnormal times, and notifies the mobile terminal.
  • the specific implementation of the artificial intelligence module is divided into two parts, the establishment of a video anomaly detection model and the application of a video anomaly detection model.
  • the first is the establishment of the video anomaly detection model. There are three parts.
  • the first part training the video data set of the video anomaly detection model for the training and learning of the subsequent machines. It includes video data of various abnormal scenes, such as frequent crossing of vehicles, robbery, trailing theft, fights, group fights, screams, crying, smoke, noisy video data, and other abnormal scenes that need to be detected.
  • the training video dataset covers most application scenarios.
  • the second part the preprocessing of the video data set.
  • the video data is extracted 10 pictures per second, and each picture is converted into a picture of 255 pixels long and 255 pixels wide.
  • the third part the establishment of training model, using artificial intelligence convolution algorithm, Python code to build the training model.
  • the model includes an input layer, a hidden layer, and an output layer.
  • the input layer is an input pre-processed picture.
  • the hidden layer is used to calculate the features of the input picture.
  • the output layer is based on the calculated features of the hidden layer to output whether the video contains abnormal scenes.
  • the training process is.
  • the normal video is marked as 0, and the abnormal video is marked as 1.
  • the abnormal video and the normal video are input into the training system at the same time, and the data set is preprocessed and the training model is calculated to distinguish whether the video is abnormal or normal.
  • the model is transferred to the server, the data set is replaced with the video of the camera, and the model is run to detect whether the video of the camera is abnormal.
  • FIG. 2 is a schematic flowchart of an object tracking method based on a high-speed ball according to an embodiment of the present invention.
  • the high-speed ball-based object tracking method S200 includes:
  • the positioning instruction is used to instruct the monitoring server to detect and target objects in the video data.
  • a positioning instruction includes an object The target object corresponding to the name.
  • the user can pre-build the shape of the specific object on the monitoring server, so The user triggers the monitoring server to issue positioning instructions, and the subsequent monitoring server can generate image shape data according to the shape of the object, where the image shape data includes several image feature points of the object.
  • the monitoring server determines the shape of the object corresponding to the image shape data according to several image feature points in the image shape data.
  • the monitoring server uses the object corresponding to the image shape data as the target object to be positioned.
  • a user inputs image shape data of a vehicle at a monitoring server, and the monitoring server parses each image feature point according to the image shape data. Secondly, the monitoring server determines that the image is a vehicle shape image according to each image feature point. Third, the monitoring server regards the vehicle as a target object to be positioned.
  • the high-speed dome integrates a gimbal system, a communication system, and a camera system, which can implement functions such as target tracking, focus adjustment, position conversion, and the like.
  • the target high-speed ball is any camera in the camera group. It can be understood that the “target” in the target high-speed ball is used to distinguish other cameras.
  • the monitoring server selects the video data of a specific camera from the camera group for detection and analysis, This particular camera is the target speed dome.
  • the "target” in the target high-speed ball is not used to limit the protection scope of the present invention, but only used for differentiation.
  • the monitoring server sequentially traverses the video data captured by the target high-speed ball according to the monitoring time, and detects the target object therefrom.
  • the monitoring server controls the PTZ of the target high-speed ball to adjust the camera lens to follow the movement of the target object according to the movement of the target object.
  • the monitoring server may draw and save the walking path of the target object, so as to provide convenience when the target object is subsequently analyzed.
  • the monitoring server can enlarge the video image containing the target object in order to obtain a more detailed picture of the target object. Or, in order to fully restore the surrounding environment of the target object at a later stage, the monitoring server may also reduce the video image containing the target object to obtain a larger field of view including the target object as much as possible.
  • the target object can automatically detect a target object for targeted shooting.
  • it can track the target object automatically, and can reduce or enlarge the video frame containing the target object, so as to provide a high-definition video frame or a larger field of view associated with the target object for the later phase.
  • the monitoring server controls the target high-speed ball to track the target object, first, the monitoring server determines whether the target video frame containing the target object matches the preset video detection abnormal model; if it matches, the target video frame is used as the tracking starting point. Starting point, control the target high-speed ball to track the target object. If they do not match, continue to determine whether the next target video frame containing the target object matches the preset video detection abnormal model.
  • the target object is a person
  • the number of high-speed balls is at least two. Different high-speed balls can photograph people from different angles.
  • the monitoring server uses the target video frame as the tracking start point. When controlling the target high-speed ball to track the target object, the monitoring server first uses the target video frame as the tracking start point to obtain the target high-speed ball to shoot the person's image.
  • the monitoring server determines whether the person image is a front image of the person, and the front image includes a face image of the person. For example, A's Trailer B, Opportunity Pickpocket B's handbag, the camera monitors A's Trailing action behavior, and sends video data containing A's Trailing action behavior to the monitoring server.
  • the monitoring server detects A's Trailing action behavior and determines A is the target person.
  • the monitoring server then analyzes the person's image according to the image analysis algorithm to determine whether there are facial feature points associated with the target person in the video data.
  • the video data contains a frontal image of the target person; if it does not exist, it considers the video data The front image of the target person is not included, and the video data includes only the back image of the target person. For example, following the above example, if the monitoring server detects the face image of A in the video data, it is considered that the target high-speed ball has captured the front image of A. If the monitoring server does not detect the face image of nail A in the video data, it considers that the target high-speed ball captured the back image of nail A.
  • the monitoring server controls the target high-speed ball to track the person; if not, the monitoring server detects an additional high-speed ball set opposite the target high-speed ball, controls the additional high-speed ball to take a frontal image of the person, and tracks the person. For example, when the monitoring server detects that the video data does not include a frontal image of the target person, the monitoring server determines the current geographic location of the target person.
  • the monitoring server detects and covers all additional high-speed domes of the target person's current geographical position and determines the installation geographic positions of all the additional high-speed domes according to the current geographic position of the target person, and determines the installation locations from all of the additional high-speed domes.
  • the target high-speed dome is an additional high-speed dome that is relatively geographically installed.
  • the monitoring server controls the extra high-speed ball relative to the installed geographical position of the target high-speed ball to track the person and take a frontal image of the person.
  • the monitoring server detects additional high speeds that are set opposite the target high-speed ball.
  • the monitoring server obtains the light intensity in the preset area.
  • a light sensor set in the preset area collects the light intensity and transmits the light intensity to the monitoring server.
  • the monitoring server judges whether the light intensity is greater than a preset intensity threshold. If it is greater than that, it obtains the minimum illumination values of all the additional high-speed balls set opposite to the target high-speed ball, and traverses the lowest illumination value from the lowest illumination values of all the additional high-speed balls.
  • the extra high-speed ball is used as a high-speed ball that tracks and captures the front image of the character. Therefore, the surveillance server obtains the front image of the character as high-definition as possible. If it is less than that, an additional high-speed ball set opposite to the target high-speed ball is detected.
  • an embodiment of the present invention provides a high-speed ball-based object tracking device applied to a monitoring server.
  • the high-speed dome-based object tracking device according to the embodiment of the present invention may be used as one of the software functional units.
  • the high-speed dome-based object tracking device includes several instructions. The several instructions are stored in a memory, and the processor may access the memory and call the instructions for execution. To complete the above-mentioned high-speed ball-based object tracking method.
  • the high-speed ball-based object tracking device 300 includes a receiving module 31, a traversal module 32, and a control module 33.
  • the receiving module 31 is configured to receive a positioning instruction, where the positioning instruction includes a target object to be positioned;
  • the traversal module 32 is configured to traverse the video data captured by the target high-speed ball according to the positioning instruction to detect the target object;
  • the control module 33 is used for controlling the target high-speed ball to track the target object, and reducing or enlarging a video picture containing the target object.
  • the target object can automatically detect a target object for targeted shooting.
  • it can track the target object automatically, and can reduce or enlarge the video frame containing the target object, so as to provide a high-definition video frame or a larger field of view associated with the target object for the later phase.
  • control module 33 includes: a judging unit 331, a control unit 332, and a continuing judging unit 333.
  • the determining unit 331 is configured to determine whether a target video frame including the target object matches a preset video detection abnormal model
  • the control unit 332 is configured to control the target high-speed ball to track the target object by using the target video frame as a tracking starting point if matched;
  • the continuing determination unit 333 is configured to continue to determine whether the target video frame of the next frame including the target object matches a preset video detection abnormal model if there is no match.
  • the above-mentioned high-speed ball-based object tracking device can execute the high-speed ball-based object tracking method provided by the embodiment of the present invention, and has corresponding function modules and beneficial effects of the execution method.
  • the high-speed ball-based object tracking device can execute the high-speed ball-based object tracking method provided by the embodiment of the present invention, and has corresponding function modules and beneficial effects of the execution method.
  • the high-speed ball-based object tracking method provided in the embodiment of the present invention.
  • an embodiment of the present invention provides a monitoring server.
  • the monitoring server 500 includes: one or more processors 51 and a memory 52. Among them, one processor 51 is taken as an example in FIG. 5.
  • the processor 51 and the memory 52 may be connected through a bus or in other manners.
  • the connection through the bus is taken as an example.
  • the memory 52 is a non-volatile computer-readable storage medium, and can be used to store non-volatile software programs, non-volatile computer executable programs, and modules, such as the high-speed ball-based object tracking method in the embodiment of the present invention. Corresponding program instructions / modules.
  • the processor 51 executes various functional applications and data processing of the high-speed dome-based object tracking device by running non-volatile software programs, instructions, and modules stored in the memory 52, that is, the high-speed dome-based Object tracking method and functions of each module of the above device embodiment.
  • the memory 52 may include a high-speed random access memory, and may further include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage device.
  • the memory 52 may optionally include a memory remotely disposed with respect to the processor 51, and these remote memories may be connected to the processor 51 through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
  • the program instructions / modules are stored in the memory 52, and when executed by the one or more processors 51, perform the high-speed ball-based object tracking method in any of the above method embodiments, for example, execute the above-described Each step in FIG. 2; the functions of each module described in FIG. 3 and FIG. 4 can also be implemented.
  • An embodiment of the present invention also provides a non-volatile computer storage medium.
  • the computer storage medium stores computer-executable instructions, and the computer-executable instructions are executed by one or more processors, such as a process in FIG. 5.
  • the processor 51 may cause the one or more processors to execute the high-speed ball-based object tracking method in any of the foregoing method embodiments, for example, to execute the high-speed ball-based object tracking method in any of the foregoing method embodiments, for example, to execute
  • the above-mentioned execution performs the above-mentioned execution of the steps shown in FIG. 2 described above; the functions of the various modules described in FIG. 3 and FIG. 4 may also be implemented.
  • the embodiments of the device or device described above are only schematic, and the unit modules described as separate components may or may not be physically separated, and the components displayed as module units may or may not be physical units. , Can be located in one place, or can be distributed to multiple network module units. Some or all of the modules may be selected according to actual needs to achieve the objective of the solution of this embodiment.

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Software Systems (AREA)
  • Signal Processing (AREA)
  • Closed-Circuit Television Systems (AREA)
  • Image Analysis (AREA)
  • Alarm Systems (AREA)

Abstract

La présente invention se rapporte au domaine technique de la vidéosurveillance et concerne en particulier un procédé de suivi d'objet basé sur une balle à grande vitesse, un serveur de surveillance et un système de vidéosurveillance. Le procédé consiste à : recevoir une instruction de positionnement, l'instruction de positionnement comprenant un objet cible devant être positionné ; selon l'instruction de positionnement, faire défiler des données vidéo capturées par une balle à grande vitesse cible de façon à détecter l'objet cible; et à commander la balle à grande vitesse cible pour suivre l'objet cible, et effectuer un zoom avant ou arrière d'une image vidéo comprenant l'objet cible. D'une part, la présente invention peut détecter automatiquement l'objet cible en vue d'effectuer une capture ciblée. D'autre part, la présente invention peut suivre automatiquement l'objet cible, et peut effectuer un zoom avant ou arrière de l'image vidéo comprenant l'objet cible, ce qui permet de fournir une image vidéo à haute définition ou un champ de vision plus large associé à l'objet cible pour un stade ultérieur.
PCT/CN2019/103776 2018-09-21 2019-08-30 Procédé de suivi d'objet basé sur une balle à grande vitesse, serveur de surveillance, et système de vidéosurveillance Ceased WO2020057353A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201811108443.7A CN109376601B (zh) 2018-09-21 2018-09-21 基于高速球的物体跟踪方法、监控服务器、视频监控系统
CN201811108443.7 2018-09-21

Publications (1)

Publication Number Publication Date
WO2020057353A1 true WO2020057353A1 (fr) 2020-03-26

Family

ID=65401703

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/103776 Ceased WO2020057353A1 (fr) 2018-09-21 2019-08-30 Procédé de suivi d'objet basé sur une balle à grande vitesse, serveur de surveillance, et système de vidéosurveillance

Country Status (2)

Country Link
CN (1) CN109376601B (fr)
WO (1) WO2020057353A1 (fr)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112104842A (zh) * 2020-09-15 2020-12-18 上海思源弘瑞自动化有限公司 图像采集设备校正方法
CN113810614A (zh) * 2021-09-22 2021-12-17 广东小天才科技有限公司 视频录制方法、装置及穿戴设备
IT202000026882A1 (it) 2020-11-10 2022-05-10 Tech4sport Srl Sistema di video tracking per la pratica sportiva
CN116437216A (zh) * 2023-06-12 2023-07-14 湖南博信创远信息科技有限公司 基于人工智能数据处理和视觉分析的工程监管方法及系统
CN119485026A (zh) * 2024-10-31 2025-02-18 天翼电信终端有限公司 视频监控方法及装置

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109376601B (zh) * 2018-09-21 2021-05-11 深圳市九洲电器有限公司 基于高速球的物体跟踪方法、监控服务器、视频监控系统
CN112004053B (zh) * 2020-07-20 2022-08-16 浙江大华技术股份有限公司 监控图像电子放大的方法、装置和计算机设备
CN114972415B (zh) * 2021-12-28 2023-03-28 广东东软学院 机器人视觉跟踪方法、系统、电子设备及介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN202190348U (zh) * 2011-04-01 2012-04-11 天津长城科安电子科技有限公司 目标自动跟踪智能摄像机
US20150229841A1 (en) * 2012-09-18 2015-08-13 Hangzhou Hikvision Digital Technology Co., Ltd. Target tracking method and system for intelligent tracking high speed dome camera
CN105245851A (zh) * 2015-10-27 2016-01-13 太原市公安局 一种视频监控系统
CN107016367A (zh) * 2017-04-06 2017-08-04 北京精英智通科技股份有限公司 一种跟踪控制方法及跟踪控制系统
CN108174152A (zh) * 2017-12-28 2018-06-15 深圳英飞拓科技股份有限公司 一种目标监控方法及目标监控系统
CN109376601A (zh) * 2018-09-21 2019-02-22 深圳市九洲电器有限公司 基于高速球的物体跟踪方法、监控服务器、视频监控系统

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101719216B (zh) * 2009-12-21 2012-01-04 西安电子科技大学 基于模板匹配的运动人体异常行为识别方法
CN102854897A (zh) * 2012-09-28 2013-01-02 上海元朔信息科技有限公司 一种异常目标发现与跟踪系统及方法
US9197861B2 (en) * 2012-11-15 2015-11-24 Avo Usa Holding 2 Corporation Multi-dimensional virtual beam detection for video analytics
CN103856707B (zh) * 2012-12-03 2017-04-19 联想(北京)有限公司 一种摄像头切换方法、装置及电子设备
US20160132722A1 (en) * 2014-05-08 2016-05-12 Santa Clara University Self-Configuring and Self-Adjusting Distributed Surveillance System
CN104253937B (zh) * 2014-10-16 2017-11-21 宁波通视电子科技有限公司 全方位摄像头
EP3275174A1 (fr) * 2015-03-23 2018-01-31 Longsand Limited Balayage facial de flux vidéo
CN104735422A (zh) * 2015-04-02 2015-06-24 重庆天量电子科技有限公司 多功能智能分析与监控系统
CN107592507A (zh) * 2017-09-29 2018-01-16 深圳市置辰海信科技有限公司 自动跟踪捕捉高清晰正面人脸照片的方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN202190348U (zh) * 2011-04-01 2012-04-11 天津长城科安电子科技有限公司 目标自动跟踪智能摄像机
US20150229841A1 (en) * 2012-09-18 2015-08-13 Hangzhou Hikvision Digital Technology Co., Ltd. Target tracking method and system for intelligent tracking high speed dome camera
CN105245851A (zh) * 2015-10-27 2016-01-13 太原市公安局 一种视频监控系统
CN107016367A (zh) * 2017-04-06 2017-08-04 北京精英智通科技股份有限公司 一种跟踪控制方法及跟踪控制系统
CN108174152A (zh) * 2017-12-28 2018-06-15 深圳英飞拓科技股份有限公司 一种目标监控方法及目标监控系统
CN109376601A (zh) * 2018-09-21 2019-02-22 深圳市九洲电器有限公司 基于高速球的物体跟踪方法、监控服务器、视频监控系统

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112104842A (zh) * 2020-09-15 2020-12-18 上海思源弘瑞自动化有限公司 图像采集设备校正方法
CN112104842B (zh) * 2020-09-15 2023-01-06 上海思源弘瑞自动化有限公司 图像采集设备校正方法、装置、设备和介质
IT202000026882A1 (it) 2020-11-10 2022-05-10 Tech4sport Srl Sistema di video tracking per la pratica sportiva
CN113810614A (zh) * 2021-09-22 2021-12-17 广东小天才科技有限公司 视频录制方法、装置及穿戴设备
CN116437216A (zh) * 2023-06-12 2023-07-14 湖南博信创远信息科技有限公司 基于人工智能数据处理和视觉分析的工程监管方法及系统
CN116437216B (zh) * 2023-06-12 2023-09-08 湖南博信创远信息科技有限公司 基于人工智能数据处理和视觉分析的工程监管方法及系统
CN119485026A (zh) * 2024-10-31 2025-02-18 天翼电信终端有限公司 视频监控方法及装置

Also Published As

Publication number Publication date
CN109376601A (zh) 2019-02-22
CN109376601B (zh) 2021-05-11

Similar Documents

Publication Publication Date Title
WO2020057355A1 (fr) Procédé et dispositif de modélisation tridimensionnelle
WO2020057346A1 (fr) Procédé et appareil de surveillance vidéo, serveur de surveillance et système de surveillance vidéo
WO2020057353A1 (fr) Procédé de suivi d'objet basé sur une balle à grande vitesse, serveur de surveillance, et système de vidéosurveillance
CN112911160B (zh) 图像拍摄方法、装置、设备及存储介质
TWI466545B (zh) 攝影機裝置及利用其進行影像監控的方法
WO2020029921A1 (fr) Procédé et dispositif de surveillance
WO2020094091A1 (fr) Procédé de capture d'image, caméra de surveillance et système de surveillance
KR101530255B1 (ko) 객체 자동 추적 장치가 구비된 cctv 시스템
JP2010009134A (ja) 画像処理システム及び画像処理方法、並びに、プログラム
JP2016100696A (ja) 画像処理装置、画像処理方法、及び画像処理システム
TW201313012A (zh) 用於決定一影像調整參數之方法及攝影機
CN103929592A (zh) 全方位智能监控设备及方法
CN112073613A (zh) 会议人像的拍摄方法、交互平板、计算机设备及存储介质
CN105554443A (zh) 视频图像中异响来源的定位方法及装置
CN107395957B (zh) 拍照方法、装置、存储介质及电子设备
CN110177258A (zh) 图像处理方法、装置、服务器及存储介质
CN109905641B (zh) 一种目标监控方法、装置、设备及系统
CN105915802A (zh) 一种转动式摄影机的拍摄范围设定调整方法
KR20230173667A (ko) Ai 기반 객체인식을 통한 감시 카메라의 셔터값 조절
CN115240107A (zh) 运动对象跟踪方法及装置、计算机可读介质和电子设备
JP2020053774A (ja) 撮像装置および画像記録方法
CN110267011B (zh) 图像处理方法、装置、服务器及存储介质
CN110191324B (zh) 图像处理方法、装置、服务器及存储介质
CN105049719A (zh) 一种全景拍摄方法及移动终端
CN116017136A (zh) 拍摄设备的控制方法和装置、存储介质及电子装置

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19862463

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS (EPO FORM 1205A DATED 10.08.2021)

122 Ep: pct application non-entry in european phase

Ref document number: 19862463

Country of ref document: EP

Kind code of ref document: A1