Extracting Human Gait Signatures by Body Segment Properties
Extracting Human Gait Signatures by Body Segment Properties
We describe a new method for extracting human gait signatures by topological analysis, using properties of body segments. The gait signature is extracted in three stages: extraction of the body contour by a thresholding and morphological filter; extraction of the leg angles based on regression analysis of contour data; and finding the body points guided by known anatomical knowledge. A 2D stick figure is used to represent the human body model, and trajectory-based kinematic features are extracted from the image sequences for describing and analyzing the gait motion. Also, the inherent periodicity in gait motion is analyzed by delay coordinates and a phase-space portrait. The utility of the proposed method is demonstrated in experiments, with comparison to medical data.
0769515371
35-39
Yoo, Jang-Hee
cbfc2f5d-2a17-4f6d-a94c-788b5747fa7b
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Harris, Chris J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
April 2002
Yoo, Jang-Hee
cbfc2f5d-2a17-4f6d-a94c-788b5747fa7b
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Harris, Chris J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Yoo, Jang-Hee, Nixon, Mark S. and Harris, Chris J.
(2002)
Extracting Human Gait Signatures by Body Segment Properties.
Proc. IEEE Southwest Symposium on Image Analysis and Interpretation.
.
Record type:
Conference or Workshop Item
(Other)
Abstract
We describe a new method for extracting human gait signatures by topological analysis, using properties of body segments. The gait signature is extracted in three stages: extraction of the body contour by a thresholding and morphological filter; extraction of the leg angles based on regression analysis of contour data; and finding the body points guided by known anatomical knowledge. A 2D stick figure is used to represent the human body model, and trajectory-based kinematic features are extracted from the image sequences for describing and analyzing the gait motion. Also, the inherent periodicity in gait motion is analyzed by delay coordinates and a phase-space portrait. The utility of the proposed method is demonstrated in experiments, with comparison to medical data.
More information
Published date: April 2002
Additional Information:
Organisation: IEEE
Venue - Dates:
Proc. IEEE Southwest Symposium on Image Analysis and Interpretation, 2002-03-31
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 256500
URI: http://eprints.soton.ac.uk/id/eprint/256500
ISBN: 0769515371
PURE UUID: a9207cfc-6f44-4b93-9a38-f36ce632582c
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Date deposited: 20 Nov 2003
Last modified: 27 Apr 2022 01:32
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Contributors
Author:
Jang-Hee Yoo
Author:
Chris J. Harris
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