Automated human recognition by gait using neural network
Automated human recognition by gait using neural network
We describe a new method for recognizing humans by their gait using back-propagation neural network. Here, the gait motion is described as rhythmic and periodic motion, and a 2D stick figure is extracted from gait silhouette by motion information with topological analysis guided by anatomical knowledge. A sequential set of 2D stick figures is used to represent the gait signature that is primitive data for the feature extraction based on motion parameters. Then, a back-propagation neural network algorithm is used to recognize humans by their gait patterns. In experiments, higher gait recognition performances have been achieved.
6 pp.-
Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
2008
Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Nixon, M.S.
(2008)
Automated human recognition by gait using neural network.
In 2008 First Workshops on Image Processing Theory, Tools and Applications.
IEEE.
.
(doi:10.1109/IPTA.2008.4743792).
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Conference or Workshop Item
(Paper)
Abstract
We describe a new method for recognizing humans by their gait using back-propagation neural network. Here, the gait motion is described as rhythmic and periodic motion, and a 2D stick figure is extracted from gait silhouette by motion information with topological analysis guided by anatomical knowledge. A sequential set of 2D stick figures is used to represent the gait signature that is primitive data for the feature extraction based on motion parameters. Then, a back-propagation neural network algorithm is used to recognize humans by their gait patterns. In experiments, higher gait recognition performances have been achieved.
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Published date: 2008
Organisations:
Southampton Wireless Group
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Local EPrints ID: 269791
URI: http://eprints.soton.ac.uk/id/eprint/269791
PURE UUID: 9069b9ee-054c-4596-973a-89964e196cd6
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Date deposited: 21 Apr 2010 07:46
Last modified: 16 Mar 2024 02:34
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