Tingfan Wu, N. Butko, Paul Ruvulo, M. Bartlett, J. Movellan
{"title":"学习做面部表情","authors":"Tingfan Wu, N. Butko, Paul Ruvulo, M. Bartlett, J. Movellan","doi":"10.1109/DEVLRN.2009.5175536","DOIUrl":null,"url":null,"abstract":"This paper explores the process of self-guided learning of realistic facial expression production by a robotic head with 31 degrees of freedom. Facial motor parameters were learned using feedback from real-time facial expression recognition from video. The experiments show that the mapping of servos to expressions was learned in under one-hour of training time. We discuss how our work may help illuminate the computational study of how infants learn to make facial expressions.","PeriodicalId":192225,"journal":{"name":"2009 IEEE 8th International Conference on Development and Learning","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"53","resultStr":"{\"title\":\"Learning to Make Facial Expressions\",\"authors\":\"Tingfan Wu, N. Butko, Paul Ruvulo, M. Bartlett, J. Movellan\",\"doi\":\"10.1109/DEVLRN.2009.5175536\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper explores the process of self-guided learning of realistic facial expression production by a robotic head with 31 degrees of freedom. Facial motor parameters were learned using feedback from real-time facial expression recognition from video. The experiments show that the mapping of servos to expressions was learned in under one-hour of training time. We discuss how our work may help illuminate the computational study of how infants learn to make facial expressions.\",\"PeriodicalId\":192225,\"journal\":{\"name\":\"2009 IEEE 8th International Conference on Development and Learning\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"53\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE 8th International Conference on Development and Learning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DEVLRN.2009.5175536\",\"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 8th International Conference on Development and Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEVLRN.2009.5175536","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper explores the process of self-guided learning of realistic facial expression production by a robotic head with 31 degrees of freedom. Facial motor parameters were learned using feedback from real-time facial expression recognition from video. The experiments show that the mapping of servos to expressions was learned in under one-hour of training time. We discuss how our work may help illuminate the computational study of how infants learn to make facial expressions.
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