Abstract
Existing joint detection and tracking algorithms generally assume one single motion model for objects of interest. However, in real world many objects have more than one motion model. In this paper we present a joint detection and tracking algorithm that is able to detect objects with multiple motion models. For such an object, a discrete variable is added into the object state to estimate its motion model. In this way, the proposed algorithm will not fail to detect objects changing their motion models as the existing algorithms. Experimental results show that our proposed algorithm has a better performance than the existing joint detection and tracking algorithms with different single motion models, in detecting objects with multiple motion models.
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Wang, Z., Zhang, H. (2010). Object Detection with Multiple Motion Models. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5996. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12297-2_18
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DOI: https://doi.org/10.1007/978-3-642-12297-2_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12296-5
Online ISBN: 978-3-642-12297-2
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