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Real-time target tracking method based on multi-feature discriminative learning

A target tracking and multi-feature technology, applied in the field of target tracking, can solve problems such as real-time occlusion, background interference, and illumination changes

Inactive Publication Date: 2018-03-13
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0007] The purpose of the present invention is to overcome the deficiencies of the prior art, and propose a stable and robust real-time target tracking method based on multi-feature discriminant learning, which can effectively solve the problems of illumination changes, background interference, and occlusion in target tracking. and low real-time issues

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  • Real-time target tracking method based on multi-feature discriminative learning
  • Real-time target tracking method based on multi-feature discriminative learning

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Embodiment Construction

[0039] The present invention will be further described below in conjunction with specific examples.

[0040] see figure 1 As shown, the real-time target tracking method based on multi-feature discriminant learning provided in this embodiment includes the following steps:

[0041] 1) Obtain the gray-scale video frame in the video, specifically: select a video sequence to be tested from the standard video library, for the obtained video sequence including T frames, start from t=1 frame, determine the target of the t-th frame data x, label it x m,n , m and n represent the row and column values ​​of the grayscale image.

[0042] 2) Use multi-dimensional features to model the tracking target, specifically: for labeled training data (x 1,1 ,y 1,1 ),......,(x m,n ,y m,n ), where x is the training sample data, y is the expected result, and it is necessary to calculate the multi-dimensional feature F f , multi-dimensional features include brightness feature CDF, texture feature ...

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Abstract

The present invention discloses a real-time target tracking method based on multi-feature discriminative learning. The method comprises the steps of: 1) acquiring a gray-scale video frame in a video,and describing a brightness attribute of a tracking target by using a Cross-bin distribution field feature; 2) using the enhanced gradient histogram feature EHOG to carry out modeling on texture diversity of the tracking target; 3) extracting the color feature CN to maintain color consistency through a color video frame in the video; 4) projecting dimensional features obtained in the steps 1), 2),and 3) into the high dimensional feature space through the Hilbert space mapping to obtain the inner product mapping; and 5) placing an obtained confidence map in the CSK framework to track, findingout a tracking target location, and then updating the template to carry out target tracking. The method disclosed by the present invention can effectively solve the problems such as light change, background interference, occlusion, low real-time performance and the like existing in target tracking.

Description

technical field [0001] The invention relates to the technical field of target tracking, in particular to a real-time target tracking method based on multi-feature discrimination learning, which can be used in intelligent video monitoring, automatic driving, human-computer interaction and the like. Background technique [0002] Object tracking is one of the most challenging problems in the field of computer vision. It plays a vital role in different applications, especially in military, medical, monitoring, and human-computer interaction. In recent years, many algorithms have been used to solve the problem of target tracking, but due to the deformation of the target, the change of illumination, and the impact of the target being occluded, the performance of the target tracking algorithm has been greatly affected. [0003] The current tracking framework can generally be divided into two modules: expression model and tracking model. In most tracking frameworks, the expression...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/246G06T7/277G06K9/62
CPCG06T7/246G06T7/277G06F18/253
Inventor 青春美邓佳丽徐向民邢晓芬
Owner SOUTH CHINA UNIV OF TECH
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