{"title":"压缩3D人脸识别应用程序","authors":"L. Granai, M. Hamouz, J. Tena, T. Vlachos","doi":"10.1109/AVSS.2007.4425282","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel 3D lossy compression algorithm tailored for 3D faces. We analyse the effects of compression on the face verification rate and measure recognition performances on the face recognition grand challenge database. Whilst preserving the spatial resolution enabling reconstruction of surface details, the proposed scheme achieves substantial compression to the extent that personal 3D biometric data could fit on a 2D barcode.","PeriodicalId":371050,"journal":{"name":"2007 IEEE Conference on Advanced Video and Signal Based Surveillance","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Compression for 3D face recognition applications\",\"authors\":\"L. Granai, M. Hamouz, J. Tena, T. Vlachos\",\"doi\":\"10.1109/AVSS.2007.4425282\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel 3D lossy compression algorithm tailored for 3D faces. We analyse the effects of compression on the face verification rate and measure recognition performances on the face recognition grand challenge database. Whilst preserving the spatial resolution enabling reconstruction of surface details, the proposed scheme achieves substantial compression to the extent that personal 3D biometric data could fit on a 2D barcode.\",\"PeriodicalId\":371050,\"journal\":{\"name\":\"2007 IEEE Conference on Advanced Video and Signal Based Surveillance\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE Conference on Advanced Video and Signal Based Surveillance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AVSS.2007.4425282\",\"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 Conference on Advanced Video and Signal Based Surveillance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AVSS.2007.4425282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper proposes a novel 3D lossy compression algorithm tailored for 3D faces. We analyse the effects of compression on the face verification rate and measure recognition performances on the face recognition grand challenge database. Whilst preserving the spatial resolution enabling reconstruction of surface details, the proposed scheme achieves substantial compression to the extent that personal 3D biometric data could fit on a 2D barcode.
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