Vision target tracking method based on sparse representation

A sparse representation and target tracking technology, applied in the field of computer vision, to achieve improved processing effects and strong robustness

Active Publication Date: 2015-07-08
HOPE CLEAN ENERGY (GRP) CO LTD
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AI Technical Summary

Problems solved by technology

But tracking objects in unrestricted everyday video remains a significant challenge

Method used

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  • Vision target tracking method based on sparse representation
  • Vision target tracking method based on sparse representation
  • Vision target tracking method based on sparse representation

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Embodiment Construction

[0043] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the implementation methods and accompanying drawings.

[0044] see figure 1 , for the actual current frame image, first judge whether the current frame is the first frame, if it is the first frame, then it needs to be based on the target image information in the first frame (the position of the target in the image, the size (the length and width are respectively W, Information such as H) obtains in advance) obtains the required decision dictionary (foreground template and background template) in the tracking method of the present invention, matching dictionary and other information, specifically: for the first frame image, at first in Figure II Template sampling is performed in the sampling area shown in , and the positive and negative templates are obtained as the training set. The positi...

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Abstract

The invention discloses a vision target tracking method based on sparse representation and belongs to the technical field of computer vision. The method includes the steps that firstly, a judgment dictionary, a matching dictionary and a gray level matrix T which are needed for following tracking processing are determined based on target images, image frames to be tracked are tracked, multiple first candidate image sample sets are sampled, K representative cluster centers are selected through K mean value clustering, the confidence values of the cluster centers are calculated based on the judgment dictionary, a sample center is set based on the largest confidence value so as to acquire second candidate image sample sets, N candidate images with the highest confidence values are selected from the sets, a gray level matrix of the candidate images is sampled on the basis of the matching dictionary and through fragments, and the candidate image with the highest similarity to the gray level matrix T serves as the tracking target of the current frame. The method is applied to the intelligent monitoring field and has the high robustness on the aspects of tracked target posture change, environment illumination change and blockage and the like.

Description

technical field [0001] The invention belongs to the field of computer vision, specifically relates to the field of intelligent monitoring, in particular to a visual target tracking based on sparse representation. Background technique [0002] Vision-based target tracking technology (generally refers to target tracking based on video or image sequences) is to detect, extract, identify and track the target object in a series of images, so as to obtain the relevant parameters of the target object, such as position , speed, scale, trajectory, etc.; further processing and analysis based on the tracking results, to realize the behavioral understanding of the target object, or to complete higher-level tasks. This is a rapidly rising hot field, which belongs to the research category of computer vision, and has broad application prospects and scientific research value. After nearly 20 to 30 years of development, various tracking algorithms have emerged at home and abroad, including ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20G06K9/62
Inventor 解梅张碧武何磊卜英家
Owner HOPE CLEAN ENERGY (GRP) CO LTD
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