J. A. Jaramillo, M. Orozco, G. Castellanos, J. Riano
{"title":"基于遗传算法的变分形状唇姿识别模型","authors":"J. A. Jaramillo, M. Orozco, G. Castellanos, J. Riano","doi":"10.1109/CERMA.2006.98","DOIUrl":null,"url":null,"abstract":"A system for feature extraction and recognition of lip postures is presented, by constructing a shape model of the inner and outer contours of the lips, whose parameters are controlled by a canonical genetic algorithm. Features of each posture are the model parameters which better fit to the analyzed image. A Bayesian classifier is used to classify, under the assumption that there is equiprobability between the classes, obtaining results up to 82.4% of accurate classification","PeriodicalId":179210,"journal":{"name":"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Variational Shape Model for Lip Postures Recognition Using GA\",\"authors\":\"J. A. Jaramillo, M. Orozco, G. Castellanos, J. Riano\",\"doi\":\"10.1109/CERMA.2006.98\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A system for feature extraction and recognition of lip postures is presented, by constructing a shape model of the inner and outer contours of the lips, whose parameters are controlled by a canonical genetic algorithm. Features of each posture are the model parameters which better fit to the analyzed image. A Bayesian classifier is used to classify, under the assumption that there is equiprobability between the classes, obtaining results up to 82.4% of accurate classification\",\"PeriodicalId\":179210,\"journal\":{\"name\":\"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CERMA.2006.98\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CERMA.2006.98","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Variational Shape Model for Lip Postures Recognition Using GA
A system for feature extraction and recognition of lip postures is presented, by constructing a shape model of the inner and outer contours of the lips, whose parameters are controlled by a canonical genetic algorithm. Features of each posture are the model parameters which better fit to the analyzed image. A Bayesian classifier is used to classify, under the assumption that there is equiprobability between the classes, obtaining results up to 82.4% of accurate classification
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