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Mean shift-based video target tracking method

A target tracking and video technology, applied in the direction of TV, color TV, color TV parts, etc., can solve the problems of inability to obtain tracking results, noise interference, etc., achieve broad application prospects and development potential, improve efficiency and accuracy, Informative effect

Inactive Publication Date: 2010-12-22
SUZHOU UNIV
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Problems solved by technology

[0006] The purpose of the present invention is to provide a video target tracking method based on Mean Shift, to solve the traditional Mean Shift method in the tracking target scale change, rotation, noise interference In such complex situations, it is difficult to obtain accurate tracking results. It not only meets the real-time requirements in terms of computing speed, but also solves the problem of tracking accuracy, and has strong robustness.

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  • Mean shift-based video target tracking method
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  • Mean shift-based video target tracking method

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Embodiment

[0040] Methods as below:

[0041] (1) Construct Gaussian pyramid image and differential pyramid scale space According to the requirements of feature point extraction, we first construct a Gaussian pyramid image for the read video image, and a two-dimensional image can be expressed in the scale space of different scales as:

[0042] L(x,y,σ)=G(x,y,σ)×I(x,y)

[0043] Among them, x, y are the abscissa and ordinate of the point in the image respectively, I(x, y) is the gray value of the image at (x, y), G(x, y, σ) is the two-dimensional Gaussian kernel function, σ represents the variance of the Gaussian normal distribution, defined as the scale of change. like figure 2 As shown, the image is filtered by Gaussian kernel functions of different scales to form a Gaussian pyramid image. The difference of Gaussian (DOG: Difference-of-Gaussian) pyramid multi-scale space is obtained by subtracting two Gaussian images of adjacent scales.

[0044] (2) Determine key points Compare each ...

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Abstract

The invention discloses a Mean shift-based video target tracking method, which extracts the SIFT characteristics of the tracking target and then matches the SIFT characteristics of the target by the Mean-Shift algorithm to realize the target tracking. The method makes full use of the characteristics of invariance against rotation, size scaling and brightness change and high resistance against noise interference and the like. The invention not only considers the real-time performance of the algorithm, but also can well solve the problems of size scaling, object obstacle, rotation, illumination change and the like. The technology has wide application prospect and development potential in the fields of safety monitoring, automobile auxiliary movement, human body movement analysis, robot vision and so on, and can improve the real-time performance and accuracy of the target tracking.

Description

technical field [0001] The invention relates to a video target tracking method, in particular to a fast and robust video target tracking method based on Mean Shift, which belongs to the field of object recognition and tracking. Background technique [0002] Video object tracking has a wide range of applications in security monitoring, automotive assisted driving, human motion analysis, and video compression. Because the visual target itself and the surrounding environment are complex and changeable, obtaining a robust and efficient tracking method is still a very challenging research topic in computer vision. [0003] Video target tracking is to use image processing and pattern recognition methods to find the most similar part of the video sequence to the specified target image, which is a typical problem in the field of computer vision. According to current research, tracking methods can be simply divided into hypothesis-based tracking methods and feature-based tracking me...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N5/14G06T7/20G06T7/292
Inventor 吴健崔志明陈建明
Owner SUZHOU UNIV
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