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Multi-target tracking method and system based on behavior learning

A multi-target tracking and behavioral technology, applied in the field of multi-target tracking method and system based on behavioral learning, can solve the problems that cannot be applied, cannot be tracked in real time, and the overall model is not practical, so as to improve tracking accuracy and reduce tracking The effect of the error rate

Active Publication Date: 2018-10-02
TSINGHUA UNIV +1
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since this method can only process the entire existing video and cannot track in real time, it is also called offline mode
Obviously, the practicability of the overall model is not strong, and it cannot be applied to fields that require real-time processing, such as real-time monitoring and automatic driving.

Method used

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  • Multi-target tracking method and system based on behavior learning
  • Multi-target tracking method and system based on behavior learning
  • Multi-target tracking method and system based on behavior learning

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Embodiment Construction

[0058] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0059] The behavior learning-based multi-target tracking method and system according to the embodiments of the present invention will be described below with reference to the accompanying drawings.

[0060] figure 1 is a flowchart of a multi-target tracking method based on behavior learning according to an embodiment of the present invention. figure 2 It is an overall flow chart of the multi-target tracking method based on behavior learning according to an embodiment of the present invention. Such as figure 1 shown, combined with f...

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Abstract

The invention provides a multi-target tracking method and system based on behavior learning. The method comprises steps of: acquiring and detecting a target video sequence, and acquiring the size and the positional information of a tracked target candidate frame depending on a detection result; modeling a multi-target real-time tracking problem and creating a production probability model of the multi-target real-time tracking problem; for the global conditional probability items in the production probability model, performing offline training on a correctly-marked training set in order to perform global behavior prediction applicable to various scenarios, and for local conditional probability items in the production probability model, on-line training local behavior prediction for each target in real time by using the tracking data of the target prior to a current frame; obtaining the behavior prediction of the target in combination with the global behavior prediction and the local behavior prediction, and tracking the multiple targets depending on the predicted target behavior. The method and the system may keep a tracking rate while tracking the multiple targets and may significantly reduce a tracking error rate.

Description

technical field [0001] The invention relates to the technical fields of computer vision and robot navigation, in particular to a multi-target tracking method and system based on behavior learning. Background technique [0002] Object tracking has always been an important issue and research hotspot in the field of computer vision. Object tracking can be divided into single object tracking and multi-object tracking (MOT, Multi-Object Tracking) according to the number of simultaneously tracked objects. In recent years, due to the wider application of video analysis scenarios such as video surveillance, motion analysis, automatic driving, and robot navigation, the research on multi-target tracking has become more important and has more practical significance. Some important application scenarios of multi-target tracking are briefly described below: [0003] (1) Intelligent video surveillance: based on motion recognition (such as footwork-based human recognition, automatic objec...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/246
CPCG06T7/20G06T2207/10016G06T2207/20081
Inventor 季向阳但乐赵泽奇戴琼海
Owner TSINGHUA UNIV
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