Object Tracking Combining Chromatic and Spatial Features

• Main Authors: James, 孫維辰
• Other Authors: Shih-Hsuan Yang
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/8vh9n7

碩士 === 國立臺北科技大學 === 資訊工程系研究所 === 97 === Object tracking is the process of location moving objects from image sequences, which has found wide applications in object recognition, automatic surveillance, human-computer interface, visual indexing, and video coding. Conventional object-tracking techniques do not always provide reliable tracking results when the tracked object has very similar features(such as colors) to the background. To overcome this problem, in this paper we propose a series of background-suppression techniques to be integrated with the conventional CamShift algorithm. The regions in the foreground with the same colors as the background will be suppressed in the first place, and then identified and compensated by centroid weighting and region growing. We also propose using an improved color quantization scheme to increase the color discrepancy. The accuracy of a tracking algorithm is measured by the associated precision and recall rates on a frame-by-frame basis. The proposed algorithm achieves averagely more than 80% accuracy for the examined test sequences, which is significantly better than the conventional tracking algorithm based on CamShift.