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Low level recognition of human motion (or how to get your man without finding his body parts)
Abstract
The recognition of human movements such as walking, running or climbing has been approached previously by tracking a number of feature points and either classifying the trajectories directly or matching them with a high-level model of the movement. A major difficulty with these methods is acquiring and trading the requisite feature points, which are generally specific joints such as knees or angles. This requires previous recognition and/or part segmentation of the actor. We show that the recognition of walking or any repetitive motion activity can be accomplished on the basis of bottom up processing, which does not require the prior identification of specific parts, or classification of the actor. In particular, we demonstrate that repetitive motion is such a strong cue, that the moving actor can be segmented, normalized spatially and temporally, and recognized by matching against a spatiotemporal template of motion features. We have implemented a real-time system that can recognize and classify repetitive motion activities in normal gray-scale image sequences.>
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Citations
Cited by
Monocular Pedestrian Detection: Survey and Experiments
Enzweiler, M., & Gavrila, D. M. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.260 · Cited by 1,213
Human Motion Analysis: A Review
Aggarwal, J. K., & Cai, Q. (1999) · Computer Vision and Image Understanding · doi:10.1006/cviu.1998.0744 · Cited by 1,156
The representation and recognition of human movement using temporal templates
Davis, J. W., & Bobick, A. F. (2002) · Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1997.609439 · Cited by 503
Automated person recognition by walking and running via model-based approaches
Yam, C., Nixon, M. S., & Carter, J. N. (2004) · Pattern Recognition · doi:10.1016/j.patcog.2003.09.012 · Cited by 353
Real-time closed-world tracking
Intille, S. S., Davis, J. W., & Bobick, A. F. (2002) · Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1997.609402 · Cited by 256
Metadata
- Authors
- Polana, R., & Nelson, R.
- Venue
- Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects
- Publisher
- IEEE Comput. Soc. Press
- Published
- 2002-12-17
- Pages
- 77-82
- OpenAlex
- W2139593995
- Cited by
- 207
- References
- 0
- FWCI
- 9.45
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Low level recognition of human motion (or how to get your man without finding his body parts). https://app.cochat.ai/papers/10.1109/mnrao.1994.346251
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- Polana, R., & Nelson, R. (2002). Low level recognition of human motion (or how to get your man without finding his body parts). Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects. https://doi.org/10.1109/mnrao.1994.346251
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