- Title
- Action-02MCF : A robust space-time correlation filter for action recognition in clutter and adverse lighting conditions
- Creator
- Ulhaq, Anwaar; Yin, Xiaoxia; Zhang, Yunchan; Gondal, Iqbal
- Date
- 2016
- Type
- Text; Conference proceedings; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/104200
- Identifier
- vital:11048
- Identifier
-
https://doi.org/10.1007/978-3-319-48680-2_41
- Identifier
- ISBN:03029743 (ISSN); 9783319486796 (ISBN)
- Abstract
- Human actions are spatio-temporal visual events and recognizing human actions in different conditions is still a challenging computer vision problem. In this paper, we introduce a robust feature based space-time correlation filter, called Action-02MCF (0’zero-aliasing’ 2M’ Maximum Margin’) for recognizing human actions in video sequences. This filter combines (i) the sparsity of spatio-temporal feature space, (ii) generalization of maximum margin criteria, (iii) enhanced aliasing free localization performance of correlation filtering using (iv) rich context of maximally stable space-time interest points into a single classifier. Its rich multi-objective function provides robustness, generalization and recognition as a single package. Action-02MCF can simultaneously localize and classify actions of interest even in clutter and adverse imaging conditions. We evaluate the performance of our proposed filter for challenging human action datasets. Experimental results verify the performance potential of our action-filter compared to other correlation filtering based action recognition approaches. © Springer International Publishing AG 2016.; Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- Publisher
- Springer Verlag
- Relation
- 17th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2016; Lecce, Italy; 24th-27th October 2016; published in Advanced Conepts for Intelligent Vision Systems (Lecture Notes in Computer Science series) Vol. 10016 LNCS, p. 465-476
- Rights
- Copyright © Springer International Publishing AG 2016.
- Rights
- This metadata is freely available under a CCO license
- Subject
- 08 Information and Computing Sciences; Bandpass filters; Clutter (information theory); Image recognition; Motion estimation; Action recognition; Computer vision problems; Correlation filtering; Imaging conditions; Multi-objective functions; Performance potentials; Space-time correlation; Spatio temporal features; Computer vision
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