IMM/MHT fusing feature information in visual tracking |
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Authors: | Shuangquan Li Shuyan Sun Sheng Jiang Zhipei Huang Jiankang Wu |
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Affiliation: | School of Information Science and Engineering,Graduate University of Chinese Academy of Sciences,Beijing 100190,China |
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Abstract: | In multi-target tracking, Multiple Hypothesis Tracking (MHT) can effectively solve the data association problem. However, traditional MHT can not make full use of motion information. In this work, we combine MHT with Interactive Multiple Model (IMM) estimator and feature fusion. New algorithm greatly improves the tracking performance due to the fact that IMM estimator provides better estimation and feature information enhances the accuracy of data association. The new algorithm is tested by tracking tropical fish in fish container. Experimental result shows that this algorithm can significantly reduce tracking lost rate and restrain the noises with higher computational effectiveness when compares with traditional MHT. |
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Keywords: | Multiple Hypothesis Tracking (MHT) Interacting Multiple Model (IMM) Feature information fusion Data association |
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