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An efficient gait recognition based on a selective neural network ensemble

✍ Scribed by Heesung Lee; Sungjun Hong; Euntai Kim

Publisher: John Wiley and Sons
Year: 2008
Tongue: English
Weight: 325 KB
Volume: 18
Category: Article
ISSN: 0899-9457
DOI: 10.1002/ima.20136

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✦ Synopsis

Abstract

The neural network ensemble is a learning paradigm where a collection of neural networks is trained for the same task. Generally, the ensemble shows better generalization performance than a single neural network. In this article, a selective neural network ensemble is applied to gait recognition. The proposed method selects some neural network based on the minimization of generalization error. Since the selection rule is directly incorporated into the cost function, we can obtain adequate component networks to constitute an ensemble. Experiments are performed with the NLPR database to show the performance of the proposed algorithm. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 237–241, 2008; Published online in Wiley InterScience (www.interscience.wiley.com).

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