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Real-time video based lighting using GPU raytracing
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. (Computer Graphics and Image Processing)
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9424-1272
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. (Scientific Visualization)ORCID iD: 0000-0002-5220-633X
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
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2014 (English)In: Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), 2014, IEEE Signal Processing Society, 2014Conference paper, Published paper (Refereed)
Abstract [en]

The recent introduction of HDR video cameras has enabled the development of image based lighting techniques for rendering virtual objects illuminated with temporally varying real world illumination. A key challenge in this context is that rendering realistic objects illuminated with video environment maps is computationally demanding. In this work, we present a GPU based rendering system based on the NVIDIA OptiX framework, enabling real time raytracing of scenes illuminated with video environment maps. For this purpose, we explore and compare several Monte Carlo sampling approaches, including bidirectional importance sampling, multiple importance sampling and sequential Monte Carlo samplers. While previous work have focused on synthetic data and overly simple environment maps sequences, we have collected a set of real world dynamic environment map sequences using a state-of-art HDR video camera for evaluation and comparisons.

Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2014.
Series
Proceedings of the European Signal Processing Conference, ISSN 2076-1465
Keywords [en]
High dynamic range imaging, image synthesis, iamge based lighting
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-107638ISI: 000393420200327OAI: oai:DiVA.org:liu-107638DiVA, id: diva2:726212
Conference
22nd European Signal Processing Conference (EUSIPCO 2014), 1-5 September 2014, Lisbon, Portugal
Projects
VPS
Funder
Swedish Foundation for Strategic Research , IISS-0081Available from: 2014-06-17 Created: 2014-06-17 Last updated: 2018-07-19Bibliographically approved

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Kronander, JoelDahlin, JohanJönsson, DanielKok, ManonSchön, ThomasUnger, Jonas

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CiteExportLink to record
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