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dc.contributor.authorPhonkrit Chandaen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.date.accessioned2018-09-04T06:03:35Z-
dc.date.available2018-09-04T06:03:35Z-
dc.date.issued2012-10-09en_US
dc.identifier.other2-s2.0-84867062156en_US
dc.identifier.other10.1109/CSAE.2012.6272730en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84867062156&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/51509-
dc.description.abstractSign language is an important communication tool for the deaf. There are two types of Thai sign language, i.e., Thai finger spelling (a signer spells each character using their fingers) and Thai sign language (a signer uses hand gesture and face expression to represent each word). In this paper, we build a dynamic hand gesture translation system with video caption without prior hand region segmentation. In particular, we utilize the upright speed-up robust feature (U-SURF) and the dynamic time warping (DTW) to find a matched word. This Thai sign language translation system was tested on 42 words. The total number of video sequences used in the experiment is 1470. The best correct classification rate for blind test set of signer-dependent is approximately 98% whereas that of signer-semi-independent is around 76 to 79%. The best blind test result for the signer-independent is around 62 to 68%. © 2012 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.titleThai sign language translation system using upright speed-up robust feature and dynamic time warpingen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleCSAE 2012 - Proceedings, 2012 IEEE International Conference on Computer Science and Automation Engineeringen_US
article.volume2en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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