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《Tactical Missile Technology》 2014-04
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Robust Real-time Object Tracking Based on Dictionary Learning

Zhou An;Jiang Hui;Yu Jingang;Tian Jinwen;College of Automation,Huazhong University of Science and Technology;Beijing Electro-mechanical Engineering Institute;  
Through the matching of scale-invariant visual features,satisfactory tracking results can usually be obtained. However,this approach computationally is very expensive. To overcome the challenging problem,a real-time object tracking method is presented based on feature matching. In the proposed approach,multi-scale translation and rotation invariant features are extracted to build a dictionary with good robustness. And then,the target is represented by coding under this dictionary. Finally,the tracking result is obtained by exhaustively searching for the one that best matches the target model among all the candidates. Experiment results show that this method can achieve real-time and robust tracking target.
【Fund】: 国家自然科学基金资助项目(61273279)
【CateGory Index】: TP391.41
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