A Mean Shift Tracking Algorithm Based on Texture Model
NING JiFeng1,2, WU ChengKe1
1.State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an 710071 2.College of Information Engineering, Northwest SciTech University of Agriculture and Forestry, Yangling 712100
Abstract：In Mean Shift tracking algorithm, model representation of the tracked target has great influence on the results of tracking. By analyzing image features of nine uniform texture models of Local Binary Pattern (LBP), five uniform modes related to the edge and the corner are used to represent the object model, which is called FLBP8,1, and FLBP8,1 is put into Mean Shift algorithm for object tracking. The edge is combined with its texture effectively by FLBP8,1. The key pixels of object mode are extracted automatically, and a few of them are used to represent the accurate object. Thus low computational complexity is obtained. Experimental results show that the proposed algorithm gets better performance in accuracy and speed of tracking than RGB based method under complex conditions.
宁纪锋，吴成柯. 一种基于纹理模型的Mean Shift目标跟踪算法*[J]. 模式识别与人工智能, 2007, 20(5): 612-618.
NING JiFeng , WU ChengKe. A Mean Shift Tracking Algorithm Based on Texture Model. , 2007, 20(5): 612-618.
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2007, Vol. 20 
