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Without any prior about the target, the appearance is usually the only cue available in visual tracking. However, in general, the appearances are often nonstationary which may ruin the predefined visual measurements and often lead to tracking failure in practice. Thus, a natural solution is to adapt the observation model to the nonstationary appearances. However, this idea is threatened by the risk...
The changes of the target's visual appearance often lead to tracking failure in practice. Hence, trackers need to be adaptive to non-stationary appearances to achieve robust visual tracking. However, the risk of adaptation drift is common in most existing adaptation schemes. This paper describes a bi-subspace model that stipulates the interactions of two different visual cues. The visual appearance...
This paper presents a novel distributed framework for multi-target tracking with an efficient data association computation. A decentralized representation of trackerspsila motion and association variables is adopted. Considering the interleaved nature of data association and tracker filtering, the multi-target tracking is formulated as a missing data problem, and the solution is found by the proposed...
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