Recognition of hand gesture based on Gaussian mixture model

Jia, J, Jiang, J and Wang, D (2008) Recognition of hand gesture based on Gaussian mixture model In: CBMI 2008, 2008-06-18 - 2008-06-20, London, UK.

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Abstract

This paper presents a new method for gesture recognition of Human beingspsila hand. This method integrates the features of shape, color and orientation histograms, which are extracted from images, and estimate the comparability with all the different types of gestures by a proposed Expectation-Maximization algorithm in Gaussian mixture model. The classification results were presented based on the values of likelihood compared with all the types of pre-assigned images, and the performance of this approach in an experiment is shown that the proposed method works well.

Item Type:	Conference or Workshop Item (UNSPECIFIED)
Divisions :	Surrey research (other units)
Authors :	Name Email ORCID Jia, J Jiang, J jianmin.jiang@surrey.ac.uk Wang, D
Date :	2008
DOI :	10.1109/CBMI.2008.4564968
Contributors :	Contribution Name Email ORCID publisher IEEE,
Depositing User :	Symplectic Elements
Date Deposited :	17 May 2017 12:24
Last Modified :	23 Jan 2020 17:49
URI:	http://epubs.surrey.ac.uk/id/eprint/835198

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