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Target tracking method, device and system

A target tracking and target technology, applied in the field of target tracking methods, devices and systems, can solve the problems of poor occlusion processing effect, low pedestrian tracking accuracy, mutual occlusion of videos, etc., so as to improve the accuracy and reduce the probability of tracking loss. Effect

Active Publication Date: 2019-03-08
BEIJING KUANGSHI TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the limitation of the shooting angle, when there are many pedestrians or the distance between pedestrians is close, mutual occlusion is likely to occur in the video
In related pedestrian tracking methods, it can be based on traditional filters, such as KFPPK (Kalman filter and the probability product kernel) algorithm, through algorithm estimation to deal with mild occlusion problems; there is also a method based on A robust multi-target detection and tracking algorithm based on Kalman filtering, which uses pixel-level differences and aspect ratios for occlusion judgment; When non-pedestrian factors interfere, the occlusion processing effect of the above methods is poor, which leads to low pedestrian tracking accuracy

Method used

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  • Target tracking method, device and system
  • Target tracking method, device and system

Examples

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Embodiment 1

[0027] First, refer to figure 1 An example electronic system 100 for implementing the object tracking method, device and system of the embodiments of the present invention will be described.

[0028] Such as figure 1 A schematic structural diagram of an electronic system is shown, the electronic system 100 includes one or more processing devices 102, one or more storage devices 104, input devices 106, output devices 108 and one or more image acquisition devices 110, these components The interconnections are via bus system 112 and / or other forms of connection mechanisms (not shown). It should be noted that figure 1 The components and structures of the electronic system 100 shown are exemplary rather than limiting, and the electronic system may also have other components and structures as required.

[0029] The processing device 102 may be a gateway, or an intelligent terminal, or a device including a central processing unit (CPU) or other forms of processing units with data ...

Embodiment 2

[0036] This embodiment provides a target tracking method, which is executed by the processing device in the above-mentioned electronic system; the processing device may be any device or chip with data processing capability. The processing device can independently process the received information, or can be connected with a server to jointly analyze and process the information, and upload the processing results to the cloud.

[0037] Such as figure 2 As shown, the target tracking method includes the following steps:

[0038] Step S202, acquiring the current frame image;

[0039] For a piece of video data, when performing target tracking on it, the target object can be detected and identified in chronological order starting from the first frame of the video data; multiple frames of images are identified as the same target Objects of objects are identified by the same serial number or symbol to track the target object. In the actual tracking process, each frame image in the a...

Embodiment 3

[0059] This embodiment provides another target tracking method, which is implemented on the basis of the above-mentioned embodiments; in this method, the target tracking method is further described, especially the specified target that is occluded and the target that is occluded by the specified target. The tracking method of the occluded target; such as image 3 As shown, the method includes the following steps:

[0060] Step S302, acquiring the current frame image;

[0061] Step S304, detecting the target object in the current frame image through the first network model;

[0062] The first network model can detect the target object through face detection or human figure detection; usually, the detection data obtained by face detection usually includes a human face or head, and the detection data obtained by human shape detection usually includes the whole human body. It can be seen from the description of the above embodiment that target tracking needs to be realized based...

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Abstract

The invention provides a target tracking method, device and system. The method comprises the following steps of detecting a target object in a current frame image by a detection model, and judging whether the target object is a designated target or not; if yes, acquiring the tracking target matched with the specified target in the specified frame image before the current frame image; if the matching tracking targets are a plurality of, determining a designated target from the plurality of tracking targets according to the relative positions of the detection data of the plurality of tracking targets; estimating a position of a tracking target other than a specified target in a current frame image based on a position of the tracking target other than the specified target in the specified frame image among a plurality of tracking targets, determining an occluded target from the tracking target other than the specified target according to an estimation result. The invention can realize thetracking of an unoccluded target object and an occluded target, reduces the occurrence probability of tracking loss, and improves the accuracy rate of target tracking.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a target tracking method, device and system. Background technique [0002] In the field of surveillance, tracking pedestrians is of great value. Due to the limitation of shooting angle, when there are many pedestrians or the distance between pedestrians is close, mutual occlusion is easy to occur in the video. In related pedestrian tracking methods, it can be based on traditional filters, such as KFPPK (Kalman filter and the probability product kernel) algorithm, through algorithm estimation to deal with mild occlusion problems; there is also a method based on A robust multi-target detection and tracking algorithm based on Kalman filtering, which uses pixel-level differences and aspect ratios for occlusion judgment; When non-pedestrian factors interfere, the occlusion processing effect of the above methods is poor, which leads to low pedestrian tracking accurac...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V20/48G06V20/53
Inventor 何琦鲍一平
Owner BEIJING KUANGSHI TECH
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