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Single-camera multi-target tracking method based on improved graph partition model

A multi-target tracking and single-camera technology, which is applied in the field of single-camera multi-target tracking based on the improved graph partition model, can solve the problems of missed detection and wrong matching in the single-camera multi-target tracking method of the graph partition model, and reduce the number of wrong matches , Reduce the missed detection rate, improve the effect of tracking accuracy

Inactive Publication Date: 2019-10-18
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0004] In view of the defects of the prior art, the purpose of the present invention is to solve the technical problems of missed detection and wrong matching in the prior art map partition model single camera multi-target tracking method

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  • Single-camera multi-target tracking method based on improved graph partition model
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  • Single-camera multi-target tracking method based on improved graph partition model

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[0039]In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0040] Single-camera multi-target tracking is performed by batch processing. Simply put, a batch of continuous pictures with several frames is input, and the appearance features and motion features are extracted from these pictures to calculate the similarity. The most similar frames of pictures are concatenated into one People's track. However, when tracking multiple targets, it is necessary to process images of an unknown number of targets at the same time, so the amount of data processed is very large.

[0041] In order to reduce the complexity of the problem to be solved, the present invention ...

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Abstract

The invention discloses a single-camera multi-target tracking method based on an improved graph partition model, and belongs to the field of target tracking. A two-layer reasoning structure is adopted. Single-camera multi-target tracking is regarded as a graph partition problem, and a binary integer programming (BIP) is used for solving the graph partition problem. In the stage of hierarchical reasoning, a short sliding window is used in the first stage, and the same person detection box is divided into the same image partition to form short track small fragments. In the second stage, a long sliding window is used, and small track segments belonging to the same person are divided into the same image partition to form a long track. For the situation that missed detection possibly occurs near the junction of non-overlapping segments of the sliding window in the second stage, the invention provides a method for overlapping the sliding window, so that the missed detection rate is reduced,and the algorithm tracking precision is improved. Identity conversion caused by mutual shielding among targets is easy to occur during multi-target tracking, so that the invention provides a trajectory constraint method, and the occurrence of identity conversion is reduced.

Description

technical field [0001] The invention belongs to the field of target tracking, and more particularly relates to a single-camera multi-target tracking method based on an improved graph partition model. Background technique [0002] Multi-target Single camera Tracking (MTSCT) is an important part of computer vision. It studies all the position information of multiple targets of interest in a continuous video frame, and obtains the motion of all targets of interest. trajectory, and then analyze the behavior of the tracking target. [0003] Today's single-camera multi-target tracking methods have achieved some good results, including Kalman filter, particle filter, correlation filter, optimal Hungarian algorithm, binary integer programming, etc. In practical application, although methods such as Kalman filter and particle filter are often intuitive and easy to understand through probability inference, they are usually difficult to infer, so the present invention often chooses op...

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Application Information

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IPC IPC(8): G06T7/223G06K9/62
CPCG06T7/223G06T2207/10016G06T2207/30241G06F18/231
Inventor 桑农熊月高常鑫史广亚
Owner HUAZHONG UNIV OF SCI & TECH
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