{"title":"彩色图像中人脸检测与跟踪的新概率模型","authors":"M. J. Flores, Jose M. Armingol, A. D. L. Escalera","doi":"10.1109/WISP.2007.4447551","DOIUrl":null,"url":null,"abstract":"This paper presents a skin-color model and an automatic face detection system on color images. Three probability distribution functions are proposed to model the skin color: flexible generalized skew-normal distribution, skew generalized normal distribution and Gaussian mixture model, over three color spaces: CbCr, HS and H. The best model is chosen to build a system for detection and tracking face, using color information. The algorithm has been tested on several sequences of color images.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"New Probability Models for Face Detection and Tracking in Color Images\",\"authors\":\"M. J. Flores, Jose M. Armingol, A. D. L. Escalera\",\"doi\":\"10.1109/WISP.2007.4447551\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a skin-color model and an automatic face detection system on color images. Three probability distribution functions are proposed to model the skin color: flexible generalized skew-normal distribution, skew generalized normal distribution and Gaussian mixture model, over three color spaces: CbCr, HS and H. The best model is chosen to build a system for detection and tracking face, using color information. The algorithm has been tested on several sequences of color images.\",\"PeriodicalId\":164902,\"journal\":{\"name\":\"2007 IEEE International Symposium on Intelligent Signal Processing\",\"volume\":\"2016 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International Symposium on Intelligent Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WISP.2007.4447551\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Symposium on Intelligent Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISP.2007.4447551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New Probability Models for Face Detection and Tracking in Color Images
This paper presents a skin-color model and an automatic face detection system on color images. Three probability distribution functions are proposed to model the skin color: flexible generalized skew-normal distribution, skew generalized normal distribution and Gaussian mixture model, over three color spaces: CbCr, HS and H. The best model is chosen to build a system for detection and tracking face, using color information. The algorithm has been tested on several sequences of color images.
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