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Automated human recognition by gait using neural network

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.-
IEEE
Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
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. 6 pp.- . (doi:10.1109/IPTA.2008.4743792).

Record type: 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

Identifiers

Local EPrints ID: 269791
URI: https://eprints.soton.ac.uk/id/eprint/269791
PURE UUID: 9069b9ee-054c-4596-973a-89964e196cd6
ORCID for M.S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

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Date deposited: 21 Apr 2010 07:46
Last modified: 19 Jul 2019 01:24

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