Ferdinand Stefanus

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We introduce MMTrack (max-margin tracker), a single-target tracker that linearly combines constant and adaptive appearance features. We frame offline single-camera tracking as a structured output prediction task where the goal is to find a sequence of locations of the target given a video. Following recent advances in machine learning, we discriminatively(More)
In this paper, we introduce MMTrack, a hybrid single pedestrian tracking algorithm that puts together the advantages of descriptive and discriminative approaches for tracking. Specifically, we combine the idea of cluster-based appearance modeling and online tracking and employ a max-margin criterion for jointly learning the relative importance of different(More)
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