{"title":"光场3D扫描仪","authors":"Yingliang Zhang, Zhong Li, Wei Yang, Peihong Yu, Haiting Lin, Jingyi Yu","doi":"10.1109/ICCPHOT.2017.7951484","DOIUrl":null,"url":null,"abstract":"We present a novel light field structure-from-motion (SfM) framework for reliable 3D object reconstruction. Specifically, we use the light field (LF) camera such as Lytro and Raytrix as a virtual 3D scanner. We move an LF camera around the object and register between multiple LF shots. We show that applying conventional SfM on sub-aperture images is not only expensive but also unreliable due to ultra-small baseline and low image resolution. Instead, our LF-SfM scheme maps ray manifolds across LFs. Specifically, we show how rays passing through a common 3D point transform between two LFs and we develop reliable technique for extracting extrinsic parameters from this ray transform. Next, we apply a new edge-preserving stereo matching technique on individual LFs and conduct LF bundle adjustment to jointly optimize pose and geometry. Comprehensive experiments show our solution outperforms many state-of-the-art passive and even active techniques especially on topologically complex objects.","PeriodicalId":276755,"journal":{"name":"2017 IEEE International Conference on Computational Photography (ICCP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"The light field 3D scanner\",\"authors\":\"Yingliang Zhang, Zhong Li, Wei Yang, Peihong Yu, Haiting Lin, Jingyi Yu\",\"doi\":\"10.1109/ICCPHOT.2017.7951484\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a novel light field structure-from-motion (SfM) framework for reliable 3D object reconstruction. Specifically, we use the light field (LF) camera such as Lytro and Raytrix as a virtual 3D scanner. We move an LF camera around the object and register between multiple LF shots. We show that applying conventional SfM on sub-aperture images is not only expensive but also unreliable due to ultra-small baseline and low image resolution. Instead, our LF-SfM scheme maps ray manifolds across LFs. Specifically, we show how rays passing through a common 3D point transform between two LFs and we develop reliable technique for extracting extrinsic parameters from this ray transform. Next, we apply a new edge-preserving stereo matching technique on individual LFs and conduct LF bundle adjustment to jointly optimize pose and geometry. Comprehensive experiments show our solution outperforms many state-of-the-art passive and even active techniques especially on topologically complex objects.\",\"PeriodicalId\":276755,\"journal\":{\"name\":\"2017 IEEE International Conference on Computational Photography (ICCP)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Computational Photography (ICCP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPHOT.2017.7951484\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Computational Photography (ICCP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPHOT.2017.7951484","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a novel light field structure-from-motion (SfM) framework for reliable 3D object reconstruction. Specifically, we use the light field (LF) camera such as Lytro and Raytrix as a virtual 3D scanner. We move an LF camera around the object and register between multiple LF shots. We show that applying conventional SfM on sub-aperture images is not only expensive but also unreliable due to ultra-small baseline and low image resolution. Instead, our LF-SfM scheme maps ray manifolds across LFs. Specifically, we show how rays passing through a common 3D point transform between two LFs and we develop reliable technique for extracting extrinsic parameters from this ray transform. Next, we apply a new edge-preserving stereo matching technique on individual LFs and conduct LF bundle adjustment to jointly optimize pose and geometry. Comprehensive experiments show our solution outperforms many state-of-the-art passive and even active techniques especially on topologically complex objects.