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.
Cite
Text
Bobick and Johnson. "Gait Recognition Using Static, Activity-Specific Parameters." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001. doi:10.1109/CVPR.2001.990506Markdown
[Bobick and Johnson. "Gait Recognition Using Static, Activity-Specific Parameters." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001.](https://mlanthology.org/cvpr/2001/bobick2001cvpr-gait/) doi:10.1109/CVPR.2001.990506BibTeX
@inproceedings{bobick2001cvpr-gait,
title = {{Gait Recognition Using Static, Activity-Specific Parameters}},
author = {Bobick, Aaron F. and Johnson, Amos Y.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2001},
pages = {I:423-430},
doi = {10.1109/CVPR.2001.990506},
url = {https://mlanthology.org/cvpr/2001/bobick2001cvpr-gait/}
}