Sparsity-inducing dictionaries for effective action classification

Roy, Debaditya and Srinivas, M and C, Krishna Mohan (2016) Sparsity-inducing dictionaries for effective action classification. Pattern Recognition, 59. pp. 55-62. ISSN 0031-3203

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Action recognition in unconstrained videos is one of the most important challenges in computer vision. In this paper, we propose sparsity-inducing dictionaries as an effective representation for action classification in videos. We demonstrate that features obtained from sparsity based representation provide discriminative information useful for classification of action videos into various action classes. We show that the constructed dictionaries are distinct for a large number of action classes resulting in a significant improvement in classification accuracy on the HMDB51 dataset. We further demonstrate the efficacy of dictionaries and sparsity based classification on other large action video datasets like UCF50.

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IITH Creators:
IITH CreatorsORCiD
Item Type: Article
Uncontrolled Keywords: Action Classification; Dictionary Learning; Sparse Representation; Action Bank features
Subjects: Computer science > Big Data Analytics
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 14 Oct 2016 10:15
Last Modified: 15 Jun 2018 06:37
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