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In this paper we propose a novel method for human action recognition, that unifies discriminative Bag of Words (BoW)-based video representation and discriminant subspace learning. An iterative optimization scheme is proposed for sequential discriminant BoWs-based action representation and code-book adaptation based on action discrimination in a reduced dimensionality feature space where action classes...
In this paper we propose a novel framework for human action recognition based on Bag of Words (BoWs) action representation, that unifies discriminative codebook generation and discriminant subspace learning. The proposed framework is able to, naturally, incorporate several (linear or non-linear) discrimination criteria for discriminant BoWs-based action representation. An iterative optimization scheme...
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