Human biometric identification through integration of footprint and gait
Gait recognition has gained attention from the biometric community because it has a couple of advantages over other biometric methods to identify individual humans: (1) it requires no subject contact and (2) gait can be assessed from a distance when other physical measures might be obscured or not a...
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| Published in | International journal of control, automation, and systems Vol. 11; no. 4; pp. 826 - 833 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.08.2013
Springer Nature B.V 제어·로봇·시스템학회 |
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| Abstract | Gait recognition has gained attention from the biometric community because it has a couple of advantages over other biometric methods to identify individual humans: (1) it requires no subject contact and (2) gait can be assessed from a distance when other physical measures might be obscured or not available. However, objects carried or worn by a subject, notably a briefcase or overcoat, may deform the gait silhouette and significantly degrade the performance of the gait recognition system. In this paper we propose that footprint and gait information may be combined to create a new method for human identification. This method automatically partitions the gait cycle based on the footprint and fuses these two parameters at the decision level to improve accuracy. We have applied the proposed algorithm to a USF gait data set to demonstrate its performance. |
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| AbstractList | Gait recognition has gained attention from the biometric community because it has a couple of advantages over other biometric methods to identify individual humans: (1) it requires no subject contact and (2) gait can be assessed from a distance when other physical measures might be obscured or not available. However, objects carried or worn by a subject, notably a briefcase or overcoat, may deform the gait silhouette and significantly degrade the performance of the gait recognition system. In this paper we propose that footprint and gait information may be combined to create a new method for human identification. This method automatically partitions the gait cycle based on the footprint and fuses these two parameters at the decision level to improve accuracy. We have applied the proposed algorithm to a USF gait data set to demonstrate its performance. Gait recognition has gained attention from the biometric community because it has a couple of advantages over other biometric methods to identify individual humans: (1) it requires no subject contact and (2) gait can be assessed from a distance when other physical measures might be obscured or not available. However, objects carried or worn by a subject, notably a briefcase or overcoat, may deform the gait silhouette and significantly degrade the performance of the gait recognition system. In this paper we propose that footprint and gait information may be combined to create a new method for human identification. This method automatically partitions the gait cycle based on the footprint and fuses these two parameters at the decision level to improve accuracy. We have applied the proposed algorithm to a USF gait data set to demonstrate its performance.[PUBLICATION ABSTRACT] Gait recognition has gained attention from the biometric community because it has a couple of advantages over other biometric methods to identify individual humans: (1) it requires no subject contact and (2) gait can be assessed from a distance when other physical measures might be obscured or not available. However, objects carried or worn by a subject, notably a briefcase or overcoat, may deform the gait silhouette and significantly degrade the performance of the gait recognition system. In this paper we propose that footprint and gait information may be combined to create a new method for human identification. This method automatically partitions the gait cycle based on the footprint and fuses these two parameters at the decision level to improve accuracy. We have applied the proposed algorithm to a USF gait data set to demonstrate its performance. KCI Citation Count: 1 |
| Author | Kim, Euntai Hong, Sungjun Jung, Jin-Woo Lee, Byungyun Lee, Heesung |
| Author_xml | – sequence: 1 givenname: Heesung surname: Lee fullname: Lee, Heesung organization: School of Electrical and Electronic Engineering, Yonsei University – sequence: 2 givenname: Byungyun surname: Lee fullname: Lee, Byungyun organization: School of Electrical and Electronic Engineering, Yonsei University – sequence: 3 givenname: Jin-Woo surname: Jung fullname: Jung, Jin-Woo organization: Department of Computer Science and Engineering, Dongguk University – sequence: 4 givenname: Sungjun surname: Hong fullname: Hong, Sungjun organization: School of Electrical and Electronic Engineering, Yonsei University – sequence: 5 givenname: Euntai surname: Kim fullname: Kim, Euntai email: etkim@yonsei.ac.kr organization: School of Electrical and Electronic Engineering, Yonsei University |
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| CitedBy_id | crossref_primary_10_1002_masy_202000246 crossref_primary_10_2139_ssrn_3350259 crossref_primary_10_1016_j_cviu_2018_01_007 crossref_primary_10_1016_j_cosrev_2021_100432 |
| Cites_doi | 10.1006/cviu.1998.0716 10.1109/MSP.2005.1550191 10.1109/10.880106 10.1109/TIP.2004.832865 10.1016/j.neucom.2008.09.009 10.1109/TPAMI.2003.1251144 10.1109/34.598228 10.1007/s12555-009-0512-1 10.1109/TPAMI.2006.38 10.1109/JPROC.2006.886018 10.1007/s12555-009-0414-2 10.1109/TCSVT.2003.821972 10.1109/TPAMI.2005.39 10.1007/978-3-540-25948-0_90 10.1109/AFGR.2002.1004181 10.1007/3-540-44887-X_93 |
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| Copyright | Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2013 |
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| Keywords | Biometrics integration deformation gait recognition footprint recognition USF HumanID outdoor database |
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| SubjectTerms | Access control Analysis Automation Biometric identification Biometrics Communities Contact Control Discriminant analysis Engineering Footprints Fuses Gait Gait recognition Human Identification systems Intelligent and Information Systems Mechatronics Methods Pattern recognition systems Robotics Studies Walking 제어계측공학 |
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| Title | Human biometric identification through integration of footprint and gait |
| URI | https://link.springer.com/article/10.1007/s12555-011-9235-1 https://www.proquest.com/docview/1416632327 https://www.proquest.com/docview/1671576616 https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001790018 |
| Volume | 11 |
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| ispartofPNX | International Journal of Control, 2013, Automation, and Systems, 11(4), , pp.826-833 |
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