Haralick features for GEI-based human gait recognition

Lishani, Ait, Boubchir, Larbi and Bouridane, Ahmed (2014) Haralick features for GEI-based human gait recognition. In: 2014 26th International Conference on Microelectronics (ICM). IEEE, Piscataway, NJ, pp. 36-39. ISBN 978-1-4799-8153-3

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/ICM.2014.7071800

Abstract

This paper proposes a supervised feature extraction method which is able to select discriminative features for human gait recognition under the variations of clothing and carrying conditions and hence to improve the recognition performances. The proposed method is based on the use of Haralick's texture features extracted locally from three regions of Gait Energy Images. The performance has been evaluated using CASIA Gait database (dataset B). The experimental using one-against-all SVM classifier yields attractive results when compared to existing and similar techniques.

Item Type: Book Section
Uncontrolled Keywords: Gait Energy Image (GEI), Gait recognition, Haralick texture features, classification, feature extraction
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 15 Sep 2015 11:39
Last Modified: 10 Nov 2016 12:38
URI: http://nrl.northumbria.ac.uk/id/eprint/23760

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