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On Laboratory Gait Analysis via Computer Vision

On Laboratory Gait Analysis via Computer Vision
On Laboratory Gait Analysis via Computer Vision
We describe a marker-less system for analysing and classifying human gait motion by combining a statistical approach and motion tracking with topological analysis guided by anatomical knowledge. The marker-less gait analysis system consists of three stages: detection and extraction of the moving human body and its contour from image sequences; extraction of human gait motion by the joint angles and body points; and kinematic analysis and feature extraction for classifying the gait pattern. The periodic motion of human gait is described by symmetry, and a 2D stick figure is used to rep-resent the human gait model. The usefulness of proposed method is demonstrated in marker-less gait analysis with comparison to biomechanical data.
Gait Analysis, Biometrics
1 902956 31 5
109-113
Yoo, Jang-Hee
cbfc2f5d-2a17-4f6d-a94c-788b5747fa7b
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Yoo, Jang-Hee
cbfc2f5d-2a17-4f6d-a94c-788b5747fa7b
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Yoo, Jang-Hee and Nixon, Mark S. (2003) On Laboratory Gait Analysis via Computer Vision. AISB ’03 Symposium on Biologically-Inspired Machine Vision, Theory and Application, University of , Aberystwyth, UK, United Kingdom. 06 - 10 Apr 2003. pp. 109-113 .

Record type: Conference or Workshop Item (Other)

Abstract

We describe a marker-less system for analysing and classifying human gait motion by combining a statistical approach and motion tracking with topological analysis guided by anatomical knowledge. The marker-less gait analysis system consists of three stages: detection and extraction of the moving human body and its contour from image sequences; extraction of human gait motion by the joint angles and body points; and kinematic analysis and feature extraction for classifying the gait pattern. The periodic motion of human gait is described by symmetry, and a 2D stick figure is used to rep-resent the human gait model. The usefulness of proposed method is demonstrated in marker-less gait analysis with comparison to biomechanical data.

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More information

Published date: 2003
Additional Information: Event Dates: April 7-11, 2003
Venue - Dates: AISB ’03 Symposium on Biologically-Inspired Machine Vision, Theory and Application, University of , Aberystwyth, UK, United Kingdom, 2003-04-06 - 2003-04-10
Keywords: Gait Analysis, Biometrics
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 258199
URI: http://eprints.soton.ac.uk/id/eprint/258199
ISBN: 1 902956 31 5
PURE UUID: 1ae3172f-ac27-4720-ae00-518c3a81a44b
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 20 Nov 2003
Last modified: 30 Jan 2020 01:24

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Contributors

Author: Jang-Hee Yoo
Author: Mark S. Nixon ORCID iD

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