| SEDMIDUBSKÝ, Jan, Jakub VALČÍK, Michal BALÁŽIA and Pavel ZEZULA. Gait Recognition Based on Normalized Walk Cycles. In George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Charless Fowlkes, Sen Wang, Min-Hyung Choi, Stephan Mantler, Jürgen Schulze, Daniel Acevedo, Klaus Mueller, Michael Papka. Proceedings of 8th International Symposium on Visual Computing (ISVC 2012). LNCS 7432. Heidelberg: Springer-Verlag, 2012, p. 11-20. ISBN 978-3-642-33190-9. Available from: https://dx.doi.org/10.1007/978-3-642-33191-6_2. |
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@inproceedings{982503,
author = {Sedmidubský, Jan and Valčík, Jakub and Balážia, Michal and Zezula, Pavel},
address = {Heidelberg},
booktitle = {Proceedings of 8th International Symposium on Visual Computing (ISVC 2012)},
doi = {http://dx.doi.org/10.1007/978-3-642-33191-6_2},
edition = {LNCS 7432},
editor = {George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Charless Fowlkes, Sen Wang, Min-Hyung Choi, Stephan Mantler, Jürgen Schulze, Daniel Acevedo, Klaus Mueller, Michael Papka},
keywords = {gait recognition; gait pattern; similarity of gait patterns},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Heidelberg},
isbn = {978-3-642-33190-9},
pages = {11-20},
publisher = {Springer-Verlag},
title = {Gait Recognition Based on Normalized Walk Cycles},
url = {http://www.isvc.net/12/},
year = {2012}
}
TY - JOUR
ID - 982503
AU - Sedmidubský, Jan - Valčík, Jakub - Balážia, Michal - Zezula, Pavel
PY - 2012
TI - Gait Recognition Based on Normalized Walk Cycles
PB - Springer-Verlag
CY - Heidelberg
SN - 9783642331909
KW - gait recognition
KW - gait pattern
KW - similarity of gait patterns
UR - http://www.isvc.net/12/
L2 - http://www.isvc.net/12/
N2 - We focus on recognizing persons according to the way they walk. Our approach considers a human movement as a set of trajectories formed by specific anatomical landmarks, such as hips, feet, shoulders, or hands. The trajectories are used for the extraction of distance-time dependency signals that express how a distance between a pair of specific landmarks on the human body changes in time as the person walks. The collection of such signals characterizes a gait pattern of person's walk. To determine the similarity of gait patterns, we propose several functions that compare various combinations of extracted signals. The gait patterns are compared on the level of individual walk cycles in order to increase the recognition effectiveness. The results evaluated on a 3D database of walking humans achieved the recognition rate up to 96%.
ER -
SEDMIDUBSKÝ, Jan, Jakub VALČÍK, Michal BALÁŽIA and Pavel ZEZULA. Gait Recognition Based on Normalized Walk Cycles. In George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Charless Fowlkes, Sen Wang, Min-Hyung Choi, Stephan Mantler, Jürgen Schulze, Daniel Acevedo, Klaus Mueller, Michael Papka. \textit{Proceedings of 8th International Symposium on Visual Computing (ISVC 2012)}. LNCS 7432. Heidelberg: Springer-Verlag, 2012, p.~11-20. ISBN~978-3-642-33190-9. Available from: https://dx.doi.org/10.1007/978-3-642-33191-6\_{}2.
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