{"title":"嘴部运动的学习和观察生成","authors":"P. Hong, Thomas S. Huang, X. Lin","doi":"10.1109/MMSP.1998.738971","DOIUrl":null,"url":null,"abstract":"This paper presents a system for analyzing and generating human mouth motion. We apply model-based tracking to a set of typical mouth image sequences and obtain model motion sequences, which are used to build the mouth motion space by applying principal component analysis (PCA). Given an abstract description of the mouth motion in the mouth motion space, our system can generate a new mouth motion image sequence.","PeriodicalId":180426,"journal":{"name":"1998 IEEE Second Workshop on Multimedia Signal Processing (Cat. No.98EX175)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Mouth motion learning and generating from observation\",\"authors\":\"P. Hong, Thomas S. Huang, X. Lin\",\"doi\":\"10.1109/MMSP.1998.738971\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a system for analyzing and generating human mouth motion. We apply model-based tracking to a set of typical mouth image sequences and obtain model motion sequences, which are used to build the mouth motion space by applying principal component analysis (PCA). Given an abstract description of the mouth motion in the mouth motion space, our system can generate a new mouth motion image sequence.\",\"PeriodicalId\":180426,\"journal\":{\"name\":\"1998 IEEE Second Workshop on Multimedia Signal Processing (Cat. No.98EX175)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1998 IEEE Second Workshop on Multimedia Signal Processing (Cat. No.98EX175)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMSP.1998.738971\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1998 IEEE Second Workshop on Multimedia Signal Processing (Cat. No.98EX175)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.1998.738971","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mouth motion learning and generating from observation
This paper presents a system for analyzing and generating human mouth motion. We apply model-based tracking to a set of typical mouth image sequences and obtain model motion sequences, which are used to build the mouth motion space by applying principal component analysis (PCA). Given an abstract description of the mouth motion in the mouth motion space, our system can generate a new mouth motion image sequence.