Visual Tracking Algorithm Combining ORB Feature and Color Model
ZHONG Hua-Min, WANG Wei, ZHANG Hui-Hua
Key Laboratory of System Control and Information Processing of Ministry of Education of China,
Department of Automation, Shanghai Jiao Tong University, Shanghai 200240
To solve the problem of invalid tracking by traditional CAMShift owing to the background with similar colors, a dynamic visual tracking algorithm is proposed combining ORB feature and color model of the object. The ORB feature is applied to extract the initial position of the object, and a adaptive color-threshold segmentation algorithm is proposed to improve the accuracy of color model for the object. Besides, the information of ORB feature points is used to revise the search window in the tracking procedure, which improves the tracking accuracy and robustness. Furthermore, a new method is proposed to estimate whether the moving object is missing, and an iteratively updated feature template is built to relocate the disappeared target. The experiments on video sequence images demonstrate that the proposed algorithm outperforms CAMShift and other improved algorithms based on feature extraction. When the target moves at high speed, the proposed algorithm has good robustness and can find out the wrong tracking result and correct it. Moreover, the computational efficiency rises greatly to ensure the real-time performance.
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2015, Vol. 28 
