ISCAS OpenIR
accurate depth-of-field rendering using adaptive bilateral depth filtering
Wu Shang; Yu Kai; Sheng Bin; Huang Feiyue; Gao Feng; Ma Lizhuang
2012
Conference Name1st International Conference on Computational Visual Media, CVM 2012
SourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages258-265
Conference DateNovember 8, 2012 - November 10, 2012
Conference PlaceBeijing, China
Indexed TypeEI
ISSN0302-9743
ISBN9783642342622
Department(1) Department of Computer Science and Engineering Shanghai Jiao Tong University China; (2) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China; (3) Tencent Research Gumei Road 1528 Shanghai 200233 China
English AbstractReal-time depth of field (DoF) rendering is crucial to realistic image synthesis and VR applications. This paper presents a new method to simulate the depth-of-field effects with bilateral depth filtering. Unlike the traditional rendering methods that handle the depth-of-field with Gaussian filtering, we develop a new DoF filter, called adaptive bilateral depth filter, to adaptively postfilter the pixels according to their depth variance. Depth information is used to focus on the objects with edge-preserving property. Our approach can eliminate the artifacts of intensity leakage, which can generate adaptive high-quality DoF rendering effects dynamically, and can be fully implemented in GPU parallelization. © 2012 Springer-Verlag.; Real-time depth of field (DoF) rendering is crucial to realistic image synthesis and VR applications. This paper presents a new method to simulate the depth-of-field effects with bilateral depth filtering. Unlike the traditional rendering methods that handle the depth-of-field with Gaussian filtering, we develop a new DoF filter, called adaptive bilateral depth filter, to adaptively postfilter the pixels according to their depth variance. Depth information is used to focus on the objects with edge-preserving property. Our approach can eliminate the artifacts of intensity leakage, which can generate adaptive high-quality DoF rendering effects dynamically, and can be fully implemented in GPU parallelization. © 2012 Springer-Verlag.
KeywordArtificial Intelligence
SponsorshipACM SIGGRAPH; China Computer Federation; Tsinghua University
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/15884
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Wu Shang,Yu Kai,Sheng Bin,et al. accurate depth-of-field rendering using adaptive bilateral depth filtering[C],2012:258-265.
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