A New Modeling Method for Gray Feature

Abstract:

The Mean-Shift algorithm has very good tracking effect when the background is in a simple; but for a complex environment, tracking effect is not very ideal. Therefore, a new gray feature modeling method is proposed in this paper. Firstly, target in the tracking window is uniformly divided into even pieces. Then the pixel gray value of each block is calculated with subtraction of certain rules. Finally, the gray value of gray difference and the whole object value fusion are fused and established the object model. The object model that established not only contains the whole gray value information, but also contains the gray value differences between regions, has a more accurate description of the target, and then distinguish target from background better. The experiment results show that: the target model using the method in this paper to track based on the Mean-Shift algorithm, has good adaptability when the target is partially occluded and has better robustness for complex background.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 3814-3817
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.3814
• Online since: May 2014
• Authors: Ming Li*, Chao Chen
• Keywords: Gray Feature, Mean-Shift, Modeling, Robustness, Suitability, Target Tracking

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