Video target tracking method based on compressed regularization block difference

A target tracking and video technology, applied in image analysis, image data processing, instruments, etc., can solve the problems of unreliability of NPD feature vector, interference of single pixel value noise, affecting the speed of video target tracking, etc.
CN107977982AActive Publication Date: 2018-05-01YUNNAN UNIV +1
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
YUNNAN UNIV
Publication Date
2018-05-01

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Abstract

The invention discloses a video target tracking method based on compressed regularization block difference. The method is realized by the steps that 1) a tracking area is selected; 2) a measurement matrix is initialized; 3) a target classifier is initialized; 4) a target classifier is updated; 5) a new video frame is input; 6) a rough candidate target set is generated; 7) CNBD characteristic vectors of all candidate targets in the rough candidate target set are calculated; 8) a rough tracking result is discriminated; 9) a fine candidate target set is generated; 10) CNBD characteristic vectorsof all candidate targets in the fine candidate target set are calculated; 11) a present-frame tracking result is discriminated; and 12) if the present frame is the last frame, tracking is completed, and otherwise, the step 4) is turned to. According to the method, differential characteristics of a compressed regularization block is used to describe the tracked or candidate targets, and the candidate target set is generated in a rough to fine sliding window manner.
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Description

technical field

[0001] The invention relates to the field of video target tracking methods, in particular to a video target tracking method based on compressed regularized block difference. Background technique

[0002] Video object tracking is to use discriminative features to track moving objects in video frame sequences to analyze their motion parameters and trajectories. However, factors such as object deformation, illumination changes, occlusion, and background chaos in actual scenes have brought great challenges to video object tracking technology. Many applications such as intelligent video surveillance, robot navigation, and human-computer interaction require video object tracking methods to be both accurate and fast.

[0003] In the whole process of the video target tracking method, prior art 1Wang N, Shi J, Yeung D Y, et al. Understanding and diagnosing visual tracking systems[C] / / Proceedings of the IEEE International Conference on Computer Vision.2015:3101-3109. ...

Claims

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