The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The recognition of human movement using temporal templates
Abstract
A view-based approach to the representation and recognition of human movement is presented. The basis of the representation is a temporal template-a static vector-image where the vector value at each point is a function of the motion properties at the corresponding spatial location in an image sequence. Using aerobics exercises as a test domain, we explore the representational power of a simple, two component version of the templates: The first value is a binary value indicating the presence of motion and the second value is a function of the recency of motion in a sequence. We then develop a recognition method matching temporal templates against stored instances of views of known actions. The method automatically performs temporal segmentation, is invariant to linear changes in speed, and runs in real-time on standard platforms.
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Citations
Cites
Recognizing human action in time-sequential images using hidden Markov model
Yamato, J., Ohya, J., & Ishii, K. (2003) · Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1992.223161 · Cited by 1,273
Cited by
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
Carreira, J., & Zisserman, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.502 · Cited by 9,570
A survey on vision-based human action recognition
Poppe, R. (2010) · Image and Vision Computing · doi:10.1016/j.imavis.2009.11.014 · Cited by 2,242
Multimodal human–computer interaction: A survey
Jaimes, A., & Sebe, N. (2007) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2006.10.019 · Cited by 965
A Comprehensive Survey of Vision-Based Human Action Recognition Methods
Zhang, H.-B., Zhang, Y.-X., Zhong, B., Lei, Q., Yang, L., Du, J.-X., & Chen, D.-S. (2019) · Sensors · doi:10.3390/s19051005 · Cited by 503
“[54], who proposed the motion energy image (MEI) and motion history image (MHI) for representing action; Zhang et al.”
BackgroundUnderstanding egocentric activities
Fathi, A., Farhadi, A., & Rehg, J. M. (2011) · 2011 International Conference on Computer Vision · doi:10.1109/iccv.2011.6126269 · Cited by 384
Metadata
- Authors
- Bobick, A. F., & Davis, J. W.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2001-03
- Volume
- 23
- Issue
- 3
- Pages
- 257-267
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2165715280
- Cited by
- 2,811
- References
- 1
- FWCI
- 42.78
- Type
- journal article
- Language
- en
- Open access
- closed
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