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Lecture Notes in Computer Science
In this paper, we present a simple yet fast and robust algorithm which exploits the dense spatio-temporal context for visual tracking. Our approach formulates the spatio-temporal relationships between the object of interest and its locally dense contexts in a Bayesian framework, which models the statistical correlation between the simple low-level features (i.e., image intensity and position) from the target and its surrounding regions. The tracking problem is then posed by computing adoi:10.1007/978-3-319-10602-1_9 fatcat:unqq53pwvfel5g3rq4fxnkmw2e