This paper presents a self-reconfigurable camera array system that captures and renders 3D virtual scenes interactively. It is composed of an array of 48 cameras mounted on mobile platforms. We propose an efficient algorithm that is capable of rendering high-quality novel views from the captured images. The algorithm reconstructs a view-dependent multiresolution 2D mesh model of the scene geometry on the fly and uses it for rendering. The algorithm combines region of interest (ROI) identification, JPEG image decompression, lens distortion correction, scene geometry reconstruction and novel view synthesis seamlessly on a single Intel Xeon 2.4 GHz processor, which is capable of generating novel views at 4 10 frames per second (fps). In addition, we present a view-dependent adaptive capturing scheme that moves the cameras in order to show even better rendering results. Such camera reconfiguration naturally leads to a nonuniform arrangement of the cameras on the camera plane, which is both view-dependent and scene-dependent.
{"title":"Multi-View Imaging: Capturing and Rendering Interactive Environments","authors":"Cha Zhang, Tsuhan Chen","doi":"10.1109/CVIIE.2005.15","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.15","url":null,"abstract":"This paper presents a self-reconfigurable camera array system that captures and renders 3D virtual scenes interactively. It is composed of an array of 48 cameras mounted on mobile platforms. We propose an efficient algorithm that is capable of rendering high-quality novel views from the captured images. The algorithm reconstructs a view-dependent multiresolution 2D mesh model of the scene geometry on the fly and uses it for rendering. The algorithm combines region of interest (ROI) identification, JPEG image decompression, lens distortion correction, scene geometry reconstruction and novel view synthesis seamlessly on a single Intel Xeon 2.4 GHz processor, which is capable of generating novel views at 4 10 frames per second (fps). In addition, we present a view-dependent adaptive capturing scheme that moves the cameras in order to show even better rendering results. Such camera reconfiguration naturally leads to a nonuniform arrangement of the cameras on the camera plane, which is both view-dependent and scene-dependent.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"38-40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123641457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Radio frequency tags allow objects to become self-describing, communicating their identity to a close at hand RF reader. Our goal is to build a radio frequency identity and geometry (RFIG) transponder that can also communicate geometry, inter-tag location history or contextsensitive user annotation.
{"title":"Tags are Coming: Exploiting Photosensing Wireless Tags for Assisting Geometric Procedures","authors":"R. Raskar, P. Beardsley, P. Dietz, J. van Baar","doi":"10.1109/CVIIE.2005.19","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.19","url":null,"abstract":"Radio frequency tags allow objects to become self-describing, communicating their identity to a close at hand RF reader. Our goal is to build a radio frequency identity and geometry (RFIG) transponder that can also communicate geometry, inter-tag location history or contextsensitive user annotation.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133622583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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