NDLI: Mahalanobis distance based Polynomial Segment Model for Chinese Sign Language Recogniton

Content Provider	IEEE Xplore Digital Library
Author	Yu Zhou Xilin Chen Debin Zhao Hongxun Yao Wen Gao
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin (Yu Zhou)
Abstract	Sign Language Recognition (SLR) systems are mostly based on Hidden Markov Model (HMM) and have achieved excellent results. However, the assumption of frame independence in HMM makes it inconsistent with the characteristic of strong temporal correlation in sign language signals. Polynomial Segment Model (PSM) explicitly represents the temporal evolution of sign language features as a Gaussian process with time-varying parameters. In this paper PSM is first introduced to SLR framework to solve the temporal correlation problem. Considering the correlation among the coefficients of polynomial trajectorypsilas different orders, Mahalanobis distance is used as the classification criterion to evaluate the likelihood of test data. Experimental results show that our method outperform the conventional HMM methods by 6.81% in recognition accuracy.
Starting Page	317
Ending Page	320
File Size	171780
Page Count	4
File Format	PDF
ISBN	9781424425709
DOI	10.1109/ICME.2008.4607435
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-23
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Handicapped aids Distance measurement Trajectory Vocabulary Euclidean distance Polynomials Mahalanobis distance Sign Language Recognition Hidden Markov Model Polynomial Segment Model
Content Type	Text
Resource Type	Article

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