Alexander Plopski, T. Mashita, K. Kiyokawa, H. Takemura
{"title":"室内AR应用的反射率和光源估计","authors":"Alexander Plopski, T. Mashita, K. Kiyokawa, H. Takemura","doi":"10.1109/VR.2014.6802072","DOIUrl":null,"url":null,"abstract":"We present an approach which enables real-time augmentation of an environment composed of materials with different texture and reflectance properties without the need of application-specific hardware or extensive preparation. Our solution uses a set of RGB images of a reconstructed model to optimize the reflectance parameters and light location. Each image is decomposed into its specular and diffuse components and we estimate the location of multiple light sources from specular highlights. The environment is stored in a voxel grid and we optimize the reflectance properties and colour of each voxel through inverse rendering. We verify our approach with a simulated environment and present results from a corresponding reconstructed environment.","PeriodicalId":408559,"journal":{"name":"2014 IEEE Virtual Reality (VR)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Reflectance and light source estimation for indoor AR Applications\",\"authors\":\"Alexander Plopski, T. Mashita, K. Kiyokawa, H. Takemura\",\"doi\":\"10.1109/VR.2014.6802072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present an approach which enables real-time augmentation of an environment composed of materials with different texture and reflectance properties without the need of application-specific hardware or extensive preparation. Our solution uses a set of RGB images of a reconstructed model to optimize the reflectance parameters and light location. Each image is decomposed into its specular and diffuse components and we estimate the location of multiple light sources from specular highlights. The environment is stored in a voxel grid and we optimize the reflectance properties and colour of each voxel through inverse rendering. We verify our approach with a simulated environment and present results from a corresponding reconstructed environment.\",\"PeriodicalId\":408559,\"journal\":{\"name\":\"2014 IEEE Virtual Reality (VR)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Virtual Reality (VR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VR.2014.6802072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Virtual Reality (VR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VR.2014.6802072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reflectance and light source estimation for indoor AR Applications
We present an approach which enables real-time augmentation of an environment composed of materials with different texture and reflectance properties without the need of application-specific hardware or extensive preparation. Our solution uses a set of RGB images of a reconstructed model to optimize the reflectance parameters and light location. Each image is decomposed into its specular and diffuse components and we estimate the location of multiple light sources from specular highlights. The environment is stored in a voxel grid and we optimize the reflectance properties and colour of each voxel through inverse rendering. We verify our approach with a simulated environment and present results from a corresponding reconstructed environment.