KLI

Classification of Korean Sign Language Alphabet Using an Accelerometer with Support Vector Machine

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Abstract
In this study, a sign language classification was developed using an accelerometer to recognize the Korean sign language alphabet. The accelerometer is worn on the proximal phalanx of the index finger of the dominant hand. Tri-axial accelerometer signals were used to segment the sign gesture (i.e., the time period when a user is performing a sign) and recognize the 31 Korean sign language letters (producing a chance level of 3.2%). The vector sum of the accelerometer signals was used to segment the sign gesture with 98.9% segmentation accuracy, which is comparable to that of previous multi-sensor systems (99.49%).
Author(s)
나영민양혜진우지환
Issued Date
2021
Type
Article
Keyword
sign languageaccelerometerclassification
DOI
10.1155/2021/9304925
URI
https://oak.ulsan.ac.kr/handle/2021.oak/8815
https://ulsan-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_cdi_doaj_primary_oai_doaj_org_article_9e595870a05b48ee92495ff350c535ae&context=PC&vid=ULSAN&lang=ko_KR&search_scope=default_scope&adaptor=primo_central_multiple_fe&tab=default_tab&query=any,contains,Classification%20of%20Korean%20Sign%20Language%20Alphabet%20Using%20an%20Accelerometer%20with%20Support%20Vector%20Machine&offset=0&pcAvailability=true
Publisher
JOURNAL OF SENSORS
Location
영국
Language
영어
ISSN
1687-725X
Citation Volume
2021
Citation Number
1
Citation Start Page
9304925
Citation End Page
930492510
Appears in Collections:
Engineering > Aerospace Engineering
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