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dc.title | Appropriateness of gait analysis for biometrics: Initial study using FDA method | en |
dc.contributor.author | Sulovská, Kateřina | |
dc.contributor.author | Fišerová, Eva | |
dc.contributor.author | Chvosteková, Martina | |
dc.contributor.author | Adámek, Milan | |
dc.relation.ispartof | Measurement: Journal of the International Measurement Confederation | |
dc.identifier.issn | 0263-2241 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.date.issued | 2017 | |
utb.relation.volume | 105 | |
dc.citation.spage | 1 | |
dc.citation.epage | 10 | |
dc.type | article | |
dc.language.iso | en | |
dc.publisher | Elsevier B.V. | |
dc.identifier.doi | 10.1016/j.measurement.2017.03.042 | |
dc.relation.uri | https://www.sciencedirect.com/science/article/pii/S0263224117302105 | |
dc.subject | Biometrics | en |
dc.subject | Functional data analysis | en |
dc.subject | Gait recognition | en |
dc.subject | Machine vision | en |
dc.subject | Pattern recognition | en |
dc.description.abstract | Human body movement has been under continuous research for many years due to its potential application as a novel biometric system to identify individuals. It is possible to utilize various techniques, not only to obtain requested movement data, but also to analyse movement data. This paper uses functional data analysis on data obtained from 12 volunteers and uses 20 markers from the 3D motion capture system VICON MX T020. The functional data analysis was chosen as a suitable tool to obtain more information about an individual's movement because it uses a technique for real-time data, which corresponds to continuous time process. The results show that all markers, under any walking speed and condition, identify a significantly high percentage of individual pairs. Further, our results discriminate between markers, where some markers are highly dependent on walking speed and condition, and also on the influence of body part asymmetry. In addition, regular movement patterns in almost all participants’ data shows a potential to identify individuals based on gait recognition with a 1:1 matching result. © 2017 Elsevier Ltd | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1007152 | |
utb.identifier.obdid | 43876406 | |
utb.identifier.scopus | 2-s2.0-85017186201 | |
utb.identifier.wok | 000401378400001 | |
utb.identifier.coden | MSRMD | |
utb.source | j-wok | |
dc.date.accessioned | 2017-08-01T08:27:21Z | |
dc.date.available | 2017-08-01T08:27:21Z | |
dc.description.sponsorship | IGA grant at Tomas Bata University in Zlin [IGA/FAI/2013/001]; European Regional Development Fund under the project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Grant Agency of the Czech Republic [GA15-06991S]; Scientific Grant Agency of the Ministry of Education of the Slovak Republic; Slovak Academy of Sciences [VEGA 2/0011/16]; Slovak Research and Development Agency [APVV-15-0295] | |
utb.ou | CEBIA-Tech | |
utb.contributor.internalauthor | Sulovská, Kateřina | |
utb.contributor.internalauthor | Adámek, Milan | |
utb.fulltext.affiliation | Kateřina Sulovská a, ⇑ , Eva Fišerová b , Martina Chvosteková c , Milan Adámek d a Tomas Bata University in Zlín, Faculty of Applied Informatics, CEBIA-Tech, Nad Stráněmi 4511, 760 05 Zlín, Czech Republic b Palacký University, Faculty of Science, Department of Mathematical Analysis and Applications of Mathematics, 17 listopadu 12, 771 46 Olomouc, Czech Republic c Slovak Academy of Sciences, Institute of Measurement Science, Dúbravská cesta 9, 841 04 Bratislava, Slovakia d Tomas Bata University in Zlín, Faculty of Applied Informatics, Department of Security Engineering, Nad Stráněmi 4511, 760 05 Zlín, Czech Republic ⇑ Corresponding author. E-mail address: sulovska@fai.utb.cz (K. Sulovská). | |
utb.fulltext.dates | Received 29 November 2016 Received in revised form 27 March 2017 Accepted 28 March 2017 Available online 2 April 2017 | |
utb.fulltext.sponsorship | This work was partly supported by the IGA grant at Tomas Bata University in Zlín (No. IGA/FAI/2013/001), the European Regional Development Fund under the project CEBIA-Tech (CZ.1.05/2.1.00/03.0089), the Grant Agency of the Czech Republic (GA15-06991S), Scientific Grant Agency of the Ministry of Education of the Slovak Republic and the Slovak Academy of Sciences (VEGA 2/0011/16) and Slovak Research and Development Agency (APVV-15-0295). The authors declare no competing financial interests. |