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Human body multiple arthrosises characteristic tracking method based on shift Mean Shift and artificial fish school intelligent optimizing

An intelligent optimization algorithm, artificial fish swarm technology, applied in character and pattern recognition, image data processing, instruments, etc.

Inactive Publication Date: 2008-04-16
HARBIN ENG UNIV
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Problems solved by technology

But so far, no one has applied the algorithm to human motion tracking

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  • Human body multiple arthrosises characteristic tracking method based on shift Mean Shift and artificial fish school intelligent optimizing
  • Human body multiple arthrosises characteristic tracking method based on shift Mean Shift and artificial fish school intelligent optimizing
  • Human body multiple arthrosises characteristic tracking method based on shift Mean Shift and artificial fish school intelligent optimizing

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Embodiment Construction

[0050] The present invention is described in more detail below in conjunction with accompanying drawing example:

[0051] The present invention is realized through the following technical solutions: first, based on the color distribution characteristics of the target model, the present invention uses the artificial fish swarm intelligent optimization algorithm to obtain the optimal position of the multi-joint characteristic target of the tracked human body in the current frame according to the information of the previous frame image , and then according to the color distribution characteristics of the target model, the MeanShift iterative algorithm is used to search for the target in the field of its optimal position, and the candidate target that is most similar to the color distribution of the target model is the tracked target.

[0052] The inventive method is described further below, and specific content is as follows:

[0053] 1. Select the Epanechnikov kernel as the kern...

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Abstract

The invention provides a human body multi-joint feature tracking method based on Mean Shift and artificial school intelligent optimization, including the following steps: firstly, based on the color distribution feature of an object model, the optimization position of a tracked human body multi-joint feature at the current frame is obtained according to the image information of a previous frame by means of artificial school intelligent optimization algorithm; then, according to the color distribution feature of the object model, object search is carried out within the domain of the optimization position by means of Mean Shift iteration algorithm, wherein, the candidate object most similar to the color distribution of the object model is the tracked object. The invention which improves the prior Mean Shift and introduces the candidate object area for artificial school intelligent optimization realizes accurate tracking of human body multi-joint feature object.

Description

(1) Technical field [0001] The invention relates to a method for adaptive human body joint target tracking based on the technical field of video images. (2) Background technology [0002] Human multi-joint feature tracking is the most challenging research direction in the current computer vision research field, and has extensive demands in some important application fields such as medical diagnosis, sports analysis and intelligent monitoring. According to different tracking objects and application scenarios, domestic and foreign scholars have proposed different tracking algorithms. The Mean Shift (MS) algorithm is a common method for detecting and tracking moving targets using color distribution. It uses density gradient climbing to find the non-parametric method of the peak of the probability distribution. [0003] In the traditional mean shift algorithm, when the moving speed of the target in the video scene is fast, and the target area overlaps between two adjacent frame...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06N3/00G06K9/46
Inventor 李金于虹丛望梁洪唐广郭卓维徐俊红周璐璐
Owner HARBIN ENG UNIV
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