Mean shift moving object tracking method based on compressed domain analysis

A moving target and target tracking technology, which is applied in the field of Meanshift moving target tracking, can solve the problems of poor algorithm effect, lack of template update algorithm, and keeping unchanged

Inactive Publication Date: 2010-10-20
WUHAN UNIV
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Problems solved by technology

[0004] The mean shift algorithm also has some shortcomings: (1) lack of necessary template update algorithm; the size of the window width remains unchanged during the tracking process, and when the target has a scale change, the tracking may fail; (2) the histogram is a relatively weak The description of the target features, when the color distribution of the background and the target is similar, the algorithm effect is not good

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  • Mean shift moving object tracking method based on compressed domain analysis
  • Mean shift moving object tracking method based on compressed domain analysis
  • Mean shift moving object tracking method based on compressed domain analysis

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Embodiment Construction

[0045] At present, the commonly used solution is to combine Kalman filter or particle filter to predict the spatial movement position of the moving target, combined with the Mean shift algorithm based on color histogram, use these two methods for tracking, and use different scale factors to divide the two The tracking result is linearly weighted to obtain the final position of the target. The idea of ​​this type of algorithm is to take into account that the target moving speed is too fast, causing the moving target to exceed the convergence range of Mean shift. If the position of the moving target in the next frame is preliminarily located by prediction, it will be used as a reference for the search center position of Mean shift, and then Perform a finer Mean shift search at the center point to accurately locate the moving target. However, this type of method requires complex filtering and prediction calculations on the image, which reduces the tracking efficiency. Considering...

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Abstract

The invention provides a Mean shift moving object tracking method based on compressed domain analysis; in the method, the compressed domain analysis and a Mean shift tracking algorithm are combined, probability statistics analysis is carried out to motion vector generated in the video coding process, so as to obtain estimated value of object moving direction and moving speed, so as to correct the central position of a Mean shift moving candidate region and lead the candidate central position to close to the central position of the practical object when the searching starts at each time. In the technical proposal, the tracking precision of the rapid moving object is improved, the searching iteration times of the algorithm are reduced, and the operation efficiency is improved. The proposal is particularly suitable for situation that the video coding and object tracking in the intelligent video monitoring equipment are carried out at the meantime.

Description

Technical field [0001] The invention belongs to the technical field of video intelligent analysis, and particularly relates to a Meanshift moving target tracking method based on video compression domain analysis. Background technique [0002] Mean shift algorithm (mean shift algorithm) is a non-parametric density estimation algorithm [1], first proposed by Fukunaga in 1975. As an efficient pattern matching algorithm, it has been successfully applied to target tracking systems with high real-time requirements [2]. Dorm Comaniciu first applied the Mean Shift algorithm to image filtering, segmentation and target tracking [3-4]. Bradski proposed the Mean shift target tracking algorithm with color histogram as the target mode [5]. The algorithm first uses the color histogram to obtain the color projection map of each frame of image, and then adaptively adjusts the position and size of the search window, and takes the obtained optimal center position as the center of the target throu...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N7/20
Inventor 胡瑞敏田纲傅佑铭王中元常军
Owner WUHAN UNIV
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