GM-PHD video multi-target tracking method fusing correlation filtering

A technology of multi-target tracking and correlation filtering, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as the decline of tracking progress

Pending Publication Date: 2021-03-23
JIANGNAN UNIV
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  • Summary
  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem that the existing multi-target tracking method decreases the tracking progress when the target is occluded, the present invention provides a GM-PHD video multi-target tracking method fused with correlation filtering, the method comprising:

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  • GM-PHD video multi-target tracking method fusing correlation filtering
  • GM-PHD video multi-target tracking method fusing correlation filtering
  • GM-PHD video multi-target tracking method fusing correlation filtering

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Embodiment 1

[0088] This embodiment provides a GM-PHD video multi-target tracking method with fusion correlation filtering, see figure 1 , the method includes:

[0089] S1: Initialization parameters; in the initial frame, the target detection frame set of the current frame is detection frame is the state vector of the i-th detection frame, where Respectively represent the abscissa and ordinate of the upper left corner of the detection frame, the width of the detection frame, the height of the detection frame and the confidence level, is the number of target detection frames in the current frame;

[0090] select The detection frame is used as the measurement of this frame Carry out the calculation of subsequent steps, c th is the confidence threshold, N k Indicates the number of measurement targets at time k, Indicates the center position and width and height information of the i-th measurement target;

[0091] Each target is represented by a rectangular box of six-dimensi...

Embodiment 2

[0097] The present embodiment provides a GM-PHD video multi-target tracking method of fusion correlation filtering, the method comprising:

[0098] Step 1: Initialize parameters, the parameters include: when the initial frame (ie k=1), the target detection frame set of the current frame is detection frame is the state vector of the i-th detection frame, where Respectively represent the abscissa and ordinate of the upper left corner of the detection frame, the width of the detection frame, the height of the detection frame and the confidence level, is the number of target detection frames in the current frame; select The detection frame is used as the measurement of this frame Carry out the calculation of subsequent steps, c th is the confidence threshold, N k Indicates the number of measurement targets at time k, Indicates the center position and width and height information of the i-th measurement target.

[0099] In a multi-target tracking system, each target i...

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Abstract

The invention discloses a GMPHD video multi-target tracking method fusing correlation filtering, and belongs to the technical field of computer vision, mode recognition and information processing. According to the method, a target is tracked by adopting a related filtering thought, and intersection ratio judgment of image information is added to carry out target template updating-free and parameter processing on the shielded target, so that pollution of a target template is reduced, and mistaken following frames are reduced. According to the method, a shielded target is put into Gaussian mixture probability hypothesis density filtering to perform position prediction updating operation, and if the target reappears in the later period, the target label is associated again, so that fragmentedtracks are reduced, and the defect of missing detection of a detector is overcome. Finally, a result on an MOT17 data set proves that compared with the best tracking algorithm GMPHDOGM17 related to GM-PHD at present, the multi-target tracking accuracy MOTA index is improved to 50.3 from the original 49.9.

Description

technical field [0001] The invention relates to a GM-PHD video multi-target tracking method with fusion correlation filtering, and belongs to the technical fields of computer vision, pattern recognition and information processing. Background technique [0002] Video multi-target tracking is an important research field in the field of computer vision, which has many applications such as intelligent surveillance, human-computer interaction, behavior recognition, robot navigation and automatic driving. Multi-object tracking can assign consistent labels to tracked objects in each video frame to produce a trajectory for each object. At present, multi-target tracking is mainly divided into two types: online tracking and batch tracking. Online tracking refers to real-time tracking using only the past and present information of the video, which is more in line with the needs of people's scenarios, and is suitable for applications with strong real-time requirements such as intellige...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/08G06N3/04
CPCG06N3/08G06V20/40G06N3/045G06F18/22G06F18/253
Inventor 杨金龙缪佳妮张媛倪鹏蒋凌云
Owner JIANGNAN UNIV
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