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Gait recognition using static, activity-specific parameters
Abstract
A gait-recognition technique that recovers static body and stride parameters of subjects as they walk is presented. This approach is an example of an activity-specific biometric: a method of extracting identifying properties of an individual or of an individual's behavior that is applicable only when a person is performing that specific action. To evaluate our parameters, we derive an expected confusion metric (related to mutual information), as opposed to reporting a percent correct with a limited database. This metric predicts how well a given feature vector will filter identity in a large population. We test the utility of a variety of body and stride parameters recovered in different viewing conditions on a database consisting of 15 to 20 subjects walking at both an angled and frontal-parallel view with respect to the camera, both indoors and out. We also analyze motion-capture data of the subjects to discover whether confusion in the parameters is inherently a physical or a visual measurement error property.
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Cited by
The humanID gait challenge problem: data sets, performance, and analysis
Sarkar, S., Phillips, P. J., Liu, Z., Vega, I. R., Grother, P., & Bowyer, K. W. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.39 · Cited by 1,133
Social signal processing: Survey of an emerging domain
Vinciarelli, A., Pantic, M., & Bourlard, H. (2009) · Image and Vision Computing · doi:10.1016/j.imavis.2008.11.007 · Cited by 842
Gait Recognition Using a View Transformation Model in the Frequency Domain
Makihara, Y., Sagawa, R., Mukaigawa, Y., Echigo, T., & Yagi, Y. (2006) · Lecture Notes in Computer Science · doi:10.1007/11744078_12 · Cited by 392
Fusion of Static and Dynamic Body Biometrics for Gait Recognition
Wang, L., Ning, H., Tan, T., & Hu, W. (2004) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2003.821972 · Cited by 377
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
Metadata
- Authors
- Bobick, A. F., & Johnson, A. Y.
- Venue
- Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001
- Publisher
- IEEE Comput. Soc
- Published
- 2005-08-25
- Volume
- 1
- Pages
- I-423-I-430
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2146968264
- Cited by
- 345
- References
- 0
- FWCI
- 46.59
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Bobick, A. F., & Johnson, A. Y. (2005). Gait recognition using static, activity-specific parameters. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001. https://doi.org/10.1109/cvpr.2001.990506
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