NDLI: Expanding Training Set for Chinese Sign Language Recognition

Content Provider	IEEE Xplore Digital Library
Author	Chunli Wang Xilin Chen Wen Gao
Copyright Year	2006
Description	Author affiliation: Sch. of Electron. & Inf. Eng., DUT, Dalian (Chunli Wang)
Abstract	In sign language recognition, one of the problems is to collect enough training data. Almost all of the statistical methods used in sign language recognition suffer from this problem. Inspired by the crossover of genetic algorithms, this paper presents a method to expand Chinese sign language (CSL) database through re-sampling from existing sign samples. Two original samples of the same sign are regarded as parents. They can reproduce their children by crossover. To verify the validity of the proposed method, some experiments are carried out on a vocabulary of 2435 gestures in Chinese sign language. Each gesture has 4 samples. Three samples are used to be the original generation. These three original samples and their offspring are used to construct the training set, and the remaining sample is used for test. The experimental results show that the new samples generated by the proposed method are effective
Starting Page	323
Ending Page	328
File Size	345581
Page Count	6
File Format	PDF
ISBN	0769525032
DOI	10.1109/FGR.2006.39
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-04-10
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Handicapped aids Vocabulary Hidden Markov models Testing Data gloves Neural networks Face recognition Data engineering Computers Training data
Content Type	Text
Resource Type	Article

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