{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/79226"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/79226","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Unstructured light fields","abstract":"We present a system for interactively acquiring and rendering light fields using a hand-held commodity camera. The main challenge we address is assisting a user in achieving good coverage of the 4D domain despite the challenges of hand-held acquisition. We define coverage by bounding reprojection error between viewpoints, which accounts for all 4 dimensions of the light field. We use this criterion together with a recent Simultaneous Localization and Mapping technique to compute a coverage map on the space of viewpoints. We provide users with real-time feedback and direct them toward under-sampled parts of the light field. Our system is lightweight and has allowed us to capture hundreds of light fields. We further present a new rendering algorithm that is tailored to the unstructured yet dense data we capture. Our method can achieve piecewise-bicubic reconstruction using a triangulation of the captured viewpoints and subdivision rules applied to reconstruction weights.","abstract_html":"We present a system for interactively acquiring and rendering light fields using a hand-held commodity camera. The main challenge we address is assisting a user in achieving good coverage of the 4D domain despite the challenges of hand-held acquisition. We define coverage by bounding reprojection error between viewpoints, which accounts for all 4 dimensions of the light field. We use this criterion together with a recent Simultaneous Localization and Mapping technique to compute a coverage map on the space of viewpoints. We provide users with real-time feedback and direct them toward under-sampled parts of the light field. Our system is lightweight and has allowed us to capture hundreds of light fields. We further present a new rendering algorithm that is tailored to the unstructured yet dense data we capture. Our method can achieve piecewise-bicubic reconstruction using a triangulation of the captured viewpoints and subdivision rules applied to reconstruction weights.","abstract_has_math":false,"creators":["Davis, Myers Abraham"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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