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Adaptive hierarchical association multi-target tracking method

A multi-target tracking and self-adaptive technology, applied in the fields of instruments, character and pattern recognition, computer parts, etc., which can solve the problems of tracking error, tracking loss, and similar appearance of the target.

Active Publication Date: 2016-08-24
NANJING UNIV OF POSTS & TELECOMM
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to solve the problem of wrong tracking and missing target caused by the similar appearance of the target that is easy to occur in the traditional layered data association technology

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Embodiment Construction

[0041] In order to make the purpose of the present invention, implementation scheme and advantage clearer, the specific implementation of the present invention is described in further detail below, and the concrete process of the present invention is as follows figure 1 shown.

[0042] A robust online hierarchical association method, specifically in accordance with the following steps:

[0043] Step 1. The video of the invention is obtained by a video surveillance system or a collection device of a video sensor network.

[0044] Step 2: Use the detector to detect the video sequence, and obtain the detection result of each frame.

[0045] Step 3. Match the detection results of the previous N frames by means of color similarity to form the initial trajectory of each target in the previous N frames, and define the tracking result of the target i in the current t-th frame as Among them, (x, y) is the center coordinate of the target area, (w, h) is the width and height of the ta...

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Abstract

The invention belongs to the technical field of smart video monitoring and provides an adaptive hierarchical association multi-target tracking method. The method is characterized by searching a protection matrix capable of separating targets as much as possible by using incremental linear discriminant analysis (ILDA); extracting the feature mean vector of each target; defining an association cost function for matching a locus with a candidate target by using the feature mean vectors so as to guide an increase in a continuous locus and a broken locus; computing a difference between a newest matching result and the feature mean vector of each locus after a previous frame is matched; and updating an ILDA module associated parameter by using the matching result when the difference is greater than a certain threshold value, or refusing to update. Compared with a method in the prior art, the method may reduce a probability of tracking an erroneous target in a multi-target tracking process because of similar appearances of the targets.

Description

technical field [0001] The invention belongs to the image analysis technology in the field of image data processing or generation, in particular to an adaptive layered association multi-target tracking method, and belongs to the technical field of intelligent video monitoring. Background technique [0002] Multi-target tracking plays an important role in computer vision systems, and has broad prospects in many fields such as human-computer interaction, military guidance, security monitoring, and intelligent transportation. [0003] In recent years, as the detection results provided by detectors have become more and more reliable, detection-based tracking methods have gradually become a major research direction for multi-object tracking. Among them, the hierarchical data association framework has attracted the attention of many people. It divides data association into two steps. The first step is local association. The traditional method is to associate the detection results ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
CPCG06V10/56G06F18/22
Inventor 胡栋张晶栾筱朋张娇
Owner NANJING UNIV OF POSTS & TELECOMM