{"title":"越南语手语阅读器使用英特尔创意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":"{\"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}","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}
Vietnamese sign language reader using Intel Creative Senz3D
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.