{"title":"Vietnamese sign language reader using Intel Creative Senz3D","authors":"V. Nguyen, M. Chew, S. Demidenko","doi":"10.1109/ICARA.2015.7081128","DOIUrl":null,"url":null,"abstract":"This paper describes a computer based system that utilizes a 3D sensor to bridge the communication barrier between hearing (and/or speech) impaired people and hearing ones. The proposed Vietnamese sign language reader successfully recognizes 28 static and 7 dynamic gestures taken from the Vietnam sign language dictionary. To recognize the gestures of a static type, various techniques have been deployed, such as Gabor Filtering, Fisher's Discriminant Analysis and Cosine Metric Distance method. The proposed technique achieves a good result with 93.89% accuracy and speed of 14 frames per second. Recognition of the dynamic gestures is based on the $1 Recognizer algorithm providing quite a good accuracy with 97.14% of accurate recognition with real-time running at 15 frames per second.","PeriodicalId":176657,"journal":{"name":"2015 6th International Conference on Automation, Robotics and Applications (ICARA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 6th International Conference on Automation, Robotics and Applications (ICARA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARA.2015.7081128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper describes a computer based system that utilizes a 3D sensor to bridge the communication barrier between hearing (and/or speech) impaired people and hearing ones. The proposed Vietnamese sign language reader successfully recognizes 28 static and 7 dynamic gestures taken from the Vietnam sign language dictionary. To recognize the gestures of a static type, various techniques have been deployed, such as Gabor Filtering, Fisher's Discriminant Analysis and Cosine Metric Distance method. The proposed technique achieves a good result with 93.89% accuracy and speed of 14 frames per second. Recognition of the dynamic gestures is based on the $1 Recognizer algorithm providing quite a good accuracy with 97.14% of accurate recognition with real-time running at 15 frames per second.