Abstract: Robust visual tracking is a challenging problem due to pose variance, occlusion and cluttered backgrounds. No single feature can be robust to all ...
PDF | On Aug 1, 2015, Ali Taalimi published Online multi-modal task-driven dictionary learning and robust joint sparse representation for visual tracking | Find
Bibliographic details on Online multi-modal task-driven dictionary learning and robust joint sparse representation for visual tracking.
TL;DR: This work proposes a tracking framework based on sparse representation and online discriminative dictionary learning, which outperforms several recently ...
May 3, 2017 · In this paper, we propose a robust tracking method based on multitask joint dictionary learning. Through extracting different features of the ...
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Multimodal dictionary learning and joint sparse ... Online multi-modal task-driven dictionary learning and robust joint sparse representation for visual tracking.
In this paper, we cast tracking as a novel multi-task multi-view sparse learning problem and exploit the cues from multiple views including various types of ...
Among different proposed sparsity constraints (priors), joint sparse representation has shown significant performance improvement in several multi-task learning ...
In our multi-task approach, particle representations are jointly sparse – only a few (but the same) dictionary templates are used to represent all the particles ...