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Human action recognition and annotation is an active research topic in computer vision. How to model various actions, varying with time resolution, visual appearance, and others, is a challenging task. In this paper, we propose a boosted exemplar learning (BEL) approach to model various actions in a weakly supervised manner, i.e., only action bag-level labels are provided but action instance level...
Human action recognition has been an active research topic in computer vision. How to model all kinds of actions, varying with time resolution, visual appearance, etc., is quite a challenging task for recognition. In this paper, we propose a Boosted Exemplar Learning (BEL) approach to recognize various actions in a weakly supervised manner, i.e., only video-based labels are provided but frame-based...
As an emerging human-computer interaction approach vision based hand interaction is more natural and efficient. However in order to achieve high accuracy, most of the existing hand posture recognition methods need a large number of labeled samples which is expensive or unavailable in practice. In this paper, a co-training based method is proposed to recognize different hand postures with a small quantity...
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