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Target tracking method based on robust PCA (principal component analysis) subspace

A target tracking and subspace technology, which is applied in the field of target tracking based on robust principal component analysis subspace, can solve problems such as more lost methods, and achieve the effect of solving occlusion problems and video blurring.

Inactive Publication Date: 2011-04-06
SHANGHAI JIAO TONG UNIV
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

First of all, the content of the template object is not updated, and the content of the first frame is fixed as the template, so that if the target object changes, the method is easy to lose

Method used

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  • Target tracking method based on robust PCA (principal component analysis) subspace
  • Target tracking method based on robust PCA (principal component analysis) subspace
  • Target tracking method based on robust PCA (principal component analysis) subspace

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Embodiment Construction

[0021] The following examples of the present invention are described in detail: the following examples are implemented on the premise of the technical solution of the present invention, and detailed implementation methods and processes are provided, but the protection scope of the present invention is not limited to the following examples.

[0022] The detailed implementation and process of this embodiment are as follows:

[0023] First, assume that the current frame is the tth frame, and the obtained subspace is U. In the current image that needs to be predicted, some candidate regions are selected by using a particle filter, which is set to x 1 , x 2 ,...,x N , where N is the total number of particles. For each particle x (assuming x i is the value of the i-th pixel), the reconstruction error can be calculated

[0024] E = Σ i = 1 n ( ...

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Abstract

The invention relates to a target tracking method based on a robust PCA (principal component analysis) subspace, belonging to the technical field of computer vision. The method comprises the following steps: calculating a predicted position by using a subspace method; extracting a target object by using the first-frame image, and establishing a subspace; generating particles, extracting images of the particles, vectorizing, projecting into the subspace, calculating a projection coefficient in accordance with PCA, and adopting an occlusion handling strategy in case that the images are subject to occlusion or image blurring; calculating the weight value of each particle based on reconstruction errors; and finally, calculating the final predicted position of the target object by a sampling method. The method of the invention can be effectively used for tracking various targets, such as faces, bodies, vehicles and other objects, and can preferably solve the problems of occlusion, video blurring, low resolution and the like.

Description

technical field [0001] The invention relates to a target tracking method in the technical field of computer vision, in particular to a target tracking method based on a robust principal component analysis (PCA) subspace. Background technique [0002] The application range of target tracking has become wider and wider, not only widely used in daily life, such as home cameras, video cameras, games, etc.; but also widely used in security monitoring equipment, especially in airports, large shopping malls, parking Fields and other places, target tracking plays a very important role. In addition, from the perspective of scientific research applications, the target tracking method is also an important basis for other applications, such as face pose estimation and expression analysis. The pros and cons of target tracking methods have become a major bottleneck restricting such applications. [0003] Generally speaking, there are many classification methods for inter-ocular tracking...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20
Inventor 俞刚卢宏涛张卿
Owner SHANGHAI JIAO TONG UNIV
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