Transform based spatio-temporal descriptors for human action recognition

Shao, Ling, Gao, Ruoyun, Liu, Yan and Zhang, Hui (2011) Transform based spatio-temporal descriptors for human action recognition. Neurocomputing, 74 (6). pp. 962-973. ISSN 0925-2312

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Official URL: http://dx.doi.org/10.1016/j.neucom.2010.11.013

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.

Item Type: Article
Uncontrolled Keywords: Transforms; Feature representation; Human action recognition; Spatio-temporal features; Feature extraction
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Related URLs:
Depositing User: Paul Burns
Date Deposited: 10 Jun 2015 15:49
Last Modified: 03 Nov 2016 12:02
URI: http://nrl.northumbria.ac.uk/id/eprint/22851

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