Combining multiple tracking algorithms for improved general performance

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摘要

Automated tracking of objects through a sequence of images has remained one of the difficult problems in computer vision. Numerous algorithms and techniques have been proposed for this task. Some algorithms perform well in restricted environments, such as tracking using stationary cameras, but a general solution is not currently available. A frequent problem is that when an algorithm is refined for one application, it becomes unsuitable for other applications. This paper proposes a general tracking system based on a different approach. Rather than refine one algorithm for a specific tracking task, two tracking algorithms are employed, and used to correct each other during the tracking task. By choosing the two algorithms such that they have complementary failure modes, a robust algorithm is created without increased specialisation.

论文关键词:Object tracking,Algorithm composition,Kalman

论文评审过程:Received 14 May 1999, Revised 16 May 2000, Accepted 16 May 2000, Available online 7 June 2001.

论文官网地址:https://doi.org/10.1016/S0031-3203(00)00072-8