Transform based spatio-temporal descriptors for human action recognition

Authors:
Ling Shao;Ruoyun Gao;Yan Liu;Hui Zhang
Affiliations:
Department of Electronic & Electrical Engineering, The University of Sheffield, UK;Department of Computer Science, Leiden University, The Netherlands;Department of Computing, Hong Kong Polytechnic University, Hong Kong, China;Department of Computer Science and Technology, United International College, Zhuhai, China and Shenzhen Key Laboratory of Intelligent Media and Speech, PKU-HKUST Shenzhen Hong Kong Institution, Sh ...
Venue:
Neurocomputing
Year:
2011

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Abstract

Classic transformation methods have been widely and efficiently used in image processing areas, such as image de-noising, image segmentation, feature detection, and compression. Based on their compact signal and image representation ability, we apply the transform based techniques on the video recognition area to extract discriminative information from each given video sequence, and use the transformed coefficients as descriptors for representing and recognizing human actions in video sequences. We validate our proposed methods on the KTH and the Hollywood datasets, which have been extensively studied by a lot of researchers. The proposed descriptors, especially the wavelet transform based descriptor, yield promising results on action recognition.