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Learning Robust Features for Gait Recognition by Maximum Margin Criterion

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BALÁŽIA, Michal and Petr SOJKA. Learning Robust Features for Gait Recognition by Maximum Margin Criterion. In Proceedings of the joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2016) and Statistical Techniques in Pattern Recognition (SPR 2016). LNCS 10029. Switzerland: Springer International Publishing AG, 2016. p. 585-586, 2 pp. ISBN 978-3-319-49054-0.
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Basic information
Original name Learning Robust Features for Gait Recognition by Maximum Margin Criterion
Authors BALÁŽIA, Michal (703 Slovakia, guarantor, belonging to the institution) and Petr SOJKA (203 Czech Republic, belonging to the institution).
Edition LNCS 10029. Switzerland, Proceedings of the joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2016) and Statistical Techniques in Pattern Recognition (SPR 2016), p. 585-586, 2 pp. 2016.
Publisher Springer International Publishing AG
Other information
Original language English
Type of outcome Proceedings paper
Field of Study Informatics
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW URL URL
RIV identification code RIV/00216224:14330/16:00091550
Organization Fakulta informatiky - Repository
ISBN 978-3-319-49054-0
ISSN 0302-9743
UT WoS 000389509300052
Keywords (in Czech) rozpoznávání podle chůze
Keywords in English gait recognition
Links MUNI/A/0892/2015. MUNI/A/0935/2015.
Changed by Changed by: RNDr. Daniel Jakubík, učo 139797. Changed: 22. 10. 2017 00:56.
Abstract
Extended abstract. The full research paper "Learning Robust Features for Gait Recognition by Maximum Margin Criterion" has been accepted for publication at the 23rd IEEE/IAPR International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, December 2016.
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