{"title":"基于快照光谱成像传感器的经济高效的新型活体面部检测技术","authors":"Zhihai Wang, Shuai Wang, Bo Gao, Tianxin Wang, Lvrong Zhao, Weixing Yu","doi":"10.1117/12.3007681","DOIUrl":null,"url":null,"abstract":"In the field of face anti-counterfeiting, there are differences between the reflection spectrum of real faces and simulated faces, which can help us overcome the shortcomings of traditional RGB cameras that are difficult to identify the authenticity of faces. In our work, we designed a face anti-spoofing imaging system based on the snapshot spectral imaging chip, which can be used in face anti-spoofing imaging through the analysis of spectral imaging data. Experiments show that our sensor could reconstruct the spectrum of the face region, establish the spectral databases, and achieve face authenticity recognition under active light source based on deep convolutional neural network, with a face recognition accuracy of 95%.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"35 2","pages":"1296315 - 1296315-6"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel cost-effective vivo facial detection technique based on snapshot spectral imaging sensor\",\"authors\":\"Zhihai Wang, Shuai Wang, Bo Gao, Tianxin Wang, Lvrong Zhao, Weixing Yu\",\"doi\":\"10.1117/12.3007681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the field of face anti-counterfeiting, there are differences between the reflection spectrum of real faces and simulated faces, which can help us overcome the shortcomings of traditional RGB cameras that are difficult to identify the authenticity of faces. In our work, we designed a face anti-spoofing imaging system based on the snapshot spectral imaging chip, which can be used in face anti-spoofing imaging through the analysis of spectral imaging data. Experiments show that our sensor could reconstruct the spectrum of the face region, establish the spectral databases, and achieve face authenticity recognition under active light source based on deep convolutional neural network, with a face recognition accuracy of 95%.\",\"PeriodicalId\":502341,\"journal\":{\"name\":\"Applied Optics and Photonics China\",\"volume\":\"35 2\",\"pages\":\"1296315 - 1296315-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Optics and Photonics China\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.3007681\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Optics and Photonics China","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.3007681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel cost-effective vivo facial detection technique based on snapshot spectral imaging sensor
In the field of face anti-counterfeiting, there are differences between the reflection spectrum of real faces and simulated faces, which can help us overcome the shortcomings of traditional RGB cameras that are difficult to identify the authenticity of faces. In our work, we designed a face anti-spoofing imaging system based on the snapshot spectral imaging chip, which can be used in face anti-spoofing imaging through the analysis of spectral imaging data. Experiments show that our sensor could reconstruct the spectrum of the face region, establish the spectral databases, and achieve face authenticity recognition under active light source based on deep convolutional neural network, with a face recognition accuracy of 95%.