Effort analysis in signer-independent sign gestures

Authors: Jiang, F.¹; Gao, W.¹; Yao, H.¹; Zhao, D.¹; Chen, X.²

Source: Journal of Experimental & Theoretical Artificial Intelligence, Volume 20, Number 2, June 2008 , pp. 133-152(20)

Publisher: Taylor and Francis Ltd

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Abstract:

A dilemma, caused by data variation, exists in research into signer-independent sign language recognition. An effective way to solve this dilemma, and thereby help push the research forward, is to understand sign language from the perspectives of human kinesics and linguistics. This paper, based on the principles of movement observation science, specifically Laban Movement Analysis (LMA), presents a summary of the factors causing sign language data variation, proposes the definition of, and a method for describing, sign language effort elements, and then provides a strategy for standardizing signer-independent sign language data. The standardized data are to be used for training and recognition. The method presented in this paper has been assessed under different experimental conditions, and the results show that the recognition accuracy is greatly increased.

Keywords: Sign gesture; Sign recognition; Effort analysis; Signer-independent; Data variance

Document Type: Research article

DOI: http://dx.doi.org/10.1080/09528130701538208

Affiliations: 1: School of Computer Science, Harbin Institute of Technology, Harbin, China 2: Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

Publication date: 2008-06-01

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