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View Invariant Gait Recognition

View Invariant Gait Recognition
View Invariant Gait Recognition
Recognition by gait is of particular interest since it is the biometric that is available at the lowest resolution, or when other biometrics are (intentionally) obscured. Gait as a biometric has now shown increasing recognition capability. There are many approaches and these show that recognition can achieve excellent performance on large databases. The majority of these approaches are planar 2D, largely since the early large databases featured subjects walking in a plane normal to the camera view. To extend deployment capability, we need viewpoint invariant gait biometrics. We describe approaches where viewpoint invariance is achieved by 3D approaches or in 2D. In the first group the identification relies on parameters extracted from the 3D body deformation during walking. These methods use several video cameras and the 3D reconstruction is achieved after a camera calibration process. On the other hand, the 2D gait biometric approaches use a single camera, usually positioned perpendicular to the subject’s walking direction. Because in real surveillance scenarios a system that operates in an unconstrained environment is necessary, many of the recent gait analysis approaches are orientated towards viewinvariant gait recognition.
978-1-84882-384-6
61-82
Springer
Seely, Richard
0b26e904-a950-4041-8234-3a6e2bea4a91
Goffredo, Michela
21a346d2-8ce6-46b7-883f-89a2c584afc7
Carter, John
e05be2f9-991d-4476-bb50-ae91606389da
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Seely, Richard
0b26e904-a950-4041-8234-3a6e2bea4a91
Goffredo, Michela
21a346d2-8ce6-46b7-883f-89a2c584afc7
Carter, John
e05be2f9-991d-4476-bb50-ae91606389da
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Seely, Richard, Goffredo, Michela, Carter, John and Nixon, Mark (2009) View Invariant Gait Recognition. In, Handbook of Remote Biometrics: for Surveillance and Security. Springer, pp. 61-82.

Record type: Book Section

Abstract

Recognition by gait is of particular interest since it is the biometric that is available at the lowest resolution, or when other biometrics are (intentionally) obscured. Gait as a biometric has now shown increasing recognition capability. There are many approaches and these show that recognition can achieve excellent performance on large databases. The majority of these approaches are planar 2D, largely since the early large databases featured subjects walking in a plane normal to the camera view. To extend deployment capability, we need viewpoint invariant gait biometrics. We describe approaches where viewpoint invariance is achieved by 3D approaches or in 2D. In the first group the identification relies on parameters extracted from the 3D body deformation during walking. These methods use several video cameras and the 3D reconstruction is achieved after a camera calibration process. On the other hand, the 2D gait biometric approaches use a single camera, usually positioned perpendicular to the subject’s walking direction. Because in real surveillance scenarios a system that operates in an unconstrained environment is necessary, many of the recent gait analysis approaches are orientated towards viewinvariant gait recognition.

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Published date: 2009
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 267083
URI: https://eprints.soton.ac.uk/id/eprint/267083
ISBN: 978-1-84882-384-6
PURE UUID: f3bbd6b3-f7bf-4edc-a00c-e99086a27fbd
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

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Date deposited: 06 Feb 2009 13:29
Last modified: 06 Jun 2018 13:18

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Contributors

Author: Richard Seely
Author: Michela Goffredo
Author: John Carter
Author: Mark Nixon ORCID iD

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