An Evaluation Framework and Database for MoCap-Based Gait Recognition Methods

@inproceedings{23249,
   author = {Balážia, Michal and Sojka, Petr},
   address = {Switzerland},
   booktitle = {Proceedings of the 1st IAPR Workshop on Reproducible Research in Pattern Recognition (RRPR 2016)},
   edition = {LNCS 10214},
   keywords = {software evaluation framework; gait cycle database; human gait recognition},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Switzerland},
   isbn = {978-3-319-56413-5},
   pages = {33-47},
   publisher = {Springer International Publishing AG},
   title = {An Evaluation Framework and Database for MoCap-Based Gait Recognition Methods},
   url = {https://wrrpr2016.sciencesconf.org},
   year = {2017}
}

TY  - JOUR
ID  - 23249
AU  - Balážia, Michal - Sojka, Petr
PY  - 2017
TI  - An Evaluation Framework and Database for MoCap-Based Gait Recognition Methods
PB  - Springer International Publishing AG
CY  - Switzerland
SN  - 9783319564135
KW  - software evaluation framework
KW  - gait cycle database
KW  - human gait recognition
UR  - https://wrrpr2016.sciencesconf.org
N2  - As a contribution to reproducible research, this paper presents a framework and a database to improve the development, evaluation and comparison of methods for gait recognition from Motion Capture (MoCap) data. The evaluation framework provides implementation details and source codes of state-of-the-art human-interpretable geometric features as well as our own approaches where gait features are learned by a modification of Fisher's Linear Discriminant Analysis with the Maximum Margin Criterion, and by a combination of Principal Component Analysis and Linear Discriminant Analysis. It includes a description and source codes of a mechanism for evaluating four class separability coefficients of feature space and four rank-based classifier performance metrics. This framework also contains a tool for learning a custom classifier and for classifying a custom query on a custom gallery. We provide an experimental database along with source codes for its extraction from the general CMU MoCap database.
ER  - 

BALÁŽIA, Michal a Petr SOJKA. \textit{An Evaluation Framework and Database for MoCap-Based Gait Recognition Methods}. In \textit{Proceedings of the 1st IAPR Workshop on Reproducible Research in Pattern Recognition (RRPR 2016)}. LNCS 10214. Switzerland: Springer International Publishing AG, 2017. s.~33-47, 15 s. ISBN~978-3-319-56413-5.