The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
O campo de luz de superfície avança as técnicas convencionais de renderização de campo de luz, utilizando informações geométricas. Usando o campo de luz de superfície, objetos do mundo real com aparência complexa podem ser representados fielmente. Esse recurso pode desempenhar um papel importante em muitas aplicações de VR/AR. No entanto, um modelo geométrico preciso é necessário para a amostragem e processamento do campo de luz superficial, o que limita seu amplo uso, uma vez que muitos objetos de interesse são difíceis de reconstruir com suas aparências geralmente muito complexas. Propomos uma nova estrutura de otimização em duas etapas para reduzir a dependência da geometria precisa. O principal insight é tratar a amostragem de campo de luz de superfície como um problema de otimização de multivisualização e multitextura. Nossa abordagem pode lidar tanto com a imprecisão do modelo quanto com o desalinhamento imagem-modelo, tornando possível criar modelos de campo de luz superficial de alta fidelidade sem usar hardware especial de alta precisão.
Wei LI
Nanjing University of Aeronautics and Astronautics
Huajun GONG
Nanjing University of Aeronautics and Astronautics
Chunlin SHEN
Nanjing University of Aeronautics and Astronautics
Yi WU
Nanjing University of Aeronautics and Astronautics
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Wei LI, Huajun GONG, Chunlin SHEN, Yi WU, "Patch Optimization for Surface Light Field Reconstruction" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 12, pp. 3267-3271, December 2018, doi: 10.1587/transinf.2018EDL8072.
Abstract: Surface light field advances conventional light field rendering techniques by utilizing geometry information. Using surface light field, real-world objects with complex appearance could be faithfully represented. This capability could play an important role in many VR/AR applications. However, an accurate geometric model is needed for surface light field sampling and processing, which limits its wide usage since many objects of interests are difficult to reconstruct with their usually very complex appearances. We propose a novel two-step optimization framework to reduce the dependency of accurate geometry. The key insight is to treat surface light field sampling as a multi-view multi-texture optimization problem. Our approach can deal with both model inaccuracy and image to model misalignment, making it possible to create high-fidelity surface light field models without using high-precision special hardware.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDL8072/_p
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@ARTICLE{e101-d_12_3267,
author={Wei LI, Huajun GONG, Chunlin SHEN, Yi WU, },
journal={IEICE TRANSACTIONS on Information},
title={Patch Optimization for Surface Light Field Reconstruction},
year={2018},
volume={E101-D},
number={12},
pages={3267-3271},
abstract={Surface light field advances conventional light field rendering techniques by utilizing geometry information. Using surface light field, real-world objects with complex appearance could be faithfully represented. This capability could play an important role in many VR/AR applications. However, an accurate geometric model is needed for surface light field sampling and processing, which limits its wide usage since many objects of interests are difficult to reconstruct with their usually very complex appearances. We propose a novel two-step optimization framework to reduce the dependency of accurate geometry. The key insight is to treat surface light field sampling as a multi-view multi-texture optimization problem. Our approach can deal with both model inaccuracy and image to model misalignment, making it possible to create high-fidelity surface light field models without using high-precision special hardware.},
keywords={},
doi={10.1587/transinf.2018EDL8072},
ISSN={1745-1361},
month={December},}
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TY - JOUR
TI - Patch Optimization for Surface Light Field Reconstruction
T2 - IEICE TRANSACTIONS on Information
SP - 3267
EP - 3271
AU - Wei LI
AU - Huajun GONG
AU - Chunlin SHEN
AU - Yi WU
PY - 2018
DO - 10.1587/transinf.2018EDL8072
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2018
AB - Surface light field advances conventional light field rendering techniques by utilizing geometry information. Using surface light field, real-world objects with complex appearance could be faithfully represented. This capability could play an important role in many VR/AR applications. However, an accurate geometric model is needed for surface light field sampling and processing, which limits its wide usage since many objects of interests are difficult to reconstruct with their usually very complex appearances. We propose a novel two-step optimization framework to reduce the dependency of accurate geometry. The key insight is to treat surface light field sampling as a multi-view multi-texture optimization problem. Our approach can deal with both model inaccuracy and image to model misalignment, making it possible to create high-fidelity surface light field models without using high-precision special hardware.
ER -