VALČÍK, Jakub, Jan SEDMIDUBSKÝ, Michal BALÁŽIA and Pavel ZEZULA. Identifying Walk Cycles for Human Recognition. In M. Chau, G. Alan Wang, Wei Thoo Yue, Hsinchun Chen. Proceedings of Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2012). LNCS 7299. Berlin: Springer-Verlag. p. 127-135. ISBN 978-3-642-30427-9. doi:10.1007/978-3-642-30428-6_10. 2012.
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Basic information
Original name Identifying Walk Cycles for Human Recognition
Authors VALČÍK, Jakub (203 Czech Republic, guarantor, belonging to the institution), Jan SEDMIDUBSKÝ (203 Czech Republic, belonging to the institution), Michal BALÁŽIA (703 Slovakia, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition LNCS 7299. Berlin, Proceedings of Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2012), p. 127-135, 9 pp. 2012.
Publisher Springer-Verlag
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Malaysia
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/12:00057307
Organization unit Faculty of Informatics
ISBN 978-3-642-30427-9
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-642-30428-6_10
Keywords in English gait recognition; walk cycle identification; time normalization; similarity distance
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. Michal Balážia, Ph.D., učo 256078. Changed: 4/1/2017 20:10.
Abstract
We concentrate on recognizing persons according to the way they walk. Our approach considers a human movement as a set of trajectories of hips, knees, and feet captured as the person walks. The trajectories are used for the extraction of viewpoint invariant planar signals that express how a distance between a pair of specific points on the human body changes in time. We solely focus on analysis and normalization of extracted signals to simplify their similarity comparison, without presenting any specific gait recognition method. In particular, we propose a novel method for automatic determination of walk cycles within extracted signals and evaluate its importance on a real-life human motion database.
Links
GBP103/12/G084, research and development projectName: Centrum pro multi-modální interpretaci dat velkého rozsahu
Investor: Czech Science Foundation
VG20122015073, research and development projectName: Efektivní vyhledávání v rozsáhlých biometrických datech (Acronym: EFBIO)
Investor: Ministry of the Interior of the CR
PrintDisplayed: 23/4/2024 11:38