- Poster presentation
- Open Access
Action recognition using Natural Action Structures
© Zhu et al; licensee BioMed Central Ltd. 2012
- Published: 16 July 2012
- Animal Model
- Structural Change
- Human Action
- Computational Modeling
- Visual System
NASs contain a variety of information about human actions and are robust against variations due to noises, occlusions, changes in scales, and a range of structural changes since they are concatenations of features at multiple spatial-temporal scales. The results suggest that NASs can be used as the basic encoding units of human actions and activities and may hold the key to the understanding of human ability of action recognition.
- Dollár P, Rabaud V, Cottrell G, Belongie S: Behavior recognition via sparse spatio-temporal features. IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS). 2005, 65-72.Google Scholar
- Yao A, Gall J, Van Gool LJ: A Hough transform-based voting framework for action recognition. IEEE Conference on Computer Vision and Pattern Recognition. 2010, 2061-2068.Google Scholar
- Niebles JC, Wang HC, Li FF: Unsupervised learning of human action categories using spatial-temporal words. International Journal of Computer Vision. 2008, 79: 299-318. 10.1007/s11263-007-0122-4.View ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.