Madhawa Gunasekara, A. Dharmarathne, D. Sandaruwan
{"title":"基于特征点的姿态变异人脸识别方法","authors":"Madhawa Gunasekara, A. Dharmarathne, D. Sandaruwan","doi":"10.1145/2636240.2636875","DOIUrl":null,"url":null,"abstract":"The Pose variation challenge with respect to missing people database scenario in computerized face recognition is addressed in this study. Moreover, relationships of 2D face images with the angle variations of 0°, 45° and 90° for the same person are obtained. A feature point based approach with geometric distances of the half of face is applied. Moreover, a mathematical model and an Artificial Neural Network model are implemented using curve fitting technique to predict the face images. The face recognition accuracy is mainly tested by using face hit ratio, with Sri Lankan test subjects.","PeriodicalId":360638,"journal":{"name":"International Symposiu on Visual Information Communication and Interaction","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Feature Point Based Approach for Pose Variant Face Recognition\",\"authors\":\"Madhawa Gunasekara, A. Dharmarathne, D. Sandaruwan\",\"doi\":\"10.1145/2636240.2636875\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Pose variation challenge with respect to missing people database scenario in computerized face recognition is addressed in this study. Moreover, relationships of 2D face images with the angle variations of 0°, 45° and 90° for the same person are obtained. A feature point based approach with geometric distances of the half of face is applied. Moreover, a mathematical model and an Artificial Neural Network model are implemented using curve fitting technique to predict the face images. The face recognition accuracy is mainly tested by using face hit ratio, with Sri Lankan test subjects.\",\"PeriodicalId\":360638,\"journal\":{\"name\":\"International Symposiu on Visual Information Communication and Interaction\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposiu on Visual Information Communication and Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2636240.2636875\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposiu on Visual Information Communication and Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2636240.2636875","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Feature Point Based Approach for Pose Variant Face Recognition
The Pose variation challenge with respect to missing people database scenario in computerized face recognition is addressed in this study. Moreover, relationships of 2D face images with the angle variations of 0°, 45° and 90° for the same person are obtained. A feature point based approach with geometric distances of the half of face is applied. Moreover, a mathematical model and an Artificial Neural Network model are implemented using curve fitting technique to predict the face images. The face recognition accuracy is mainly tested by using face hit ratio, with Sri Lankan test subjects.
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