{"title":"基于对齐的手语视频中孤立符号的提取","authors":"P. Santemiz, O. Aran, M. Saraçlar, L. Akarun","doi":"10.1109/SIU.2009.5136450","DOIUrl":null,"url":null,"abstract":"This paper presents a method to extract isolated signs from continuous sign language videos. We use sequences that approximately contain the sign that we are interested in and align the sequences to find the exact start and end frames. We compare different feature extraction methods, different alignment methods, and assess the performance of our system on a database from Turkish sign language.","PeriodicalId":219938,"journal":{"name":"2009 IEEE 17th Signal Processing and Communications Applications Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Alignment based extraction of isolated signs from sign language videos\",\"authors\":\"P. Santemiz, O. Aran, M. Saraçlar, L. Akarun\",\"doi\":\"10.1109/SIU.2009.5136450\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method to extract isolated signs from continuous sign language videos. We use sequences that approximately contain the sign that we are interested in and align the sequences to find the exact start and end frames. We compare different feature extraction methods, different alignment methods, and assess the performance of our system on a database from Turkish sign language.\",\"PeriodicalId\":219938,\"journal\":{\"name\":\"2009 IEEE 17th Signal Processing and Communications Applications Conference\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE 17th Signal Processing and Communications Applications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2009.5136450\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE 17th Signal Processing and Communications Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2009.5136450","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Alignment based extraction of isolated signs from sign language videos
This paper presents a method to extract isolated signs from continuous sign language videos. We use sequences that approximately contain the sign that we are interested in and align the sequences to find the exact start and end frames. We compare different feature extraction methods, different alignment methods, and assess the performance of our system on a database from Turkish sign language.