Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/36209
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dc.contributor.authorLIEVENS, Hendrik-
dc.contributor.authorZOOMERS, Brent-
dc.contributor.authorWIJNANTS, Maarten-
dc.contributor.authorPUT, Jeroen-
dc.contributor.authorLAMOTTE, Wim-
dc.contributor.authorQUAX, Peter-
dc.contributor.authorMICHIELS, Nick-
dc.date.accessioned2021-12-15T12:20:16Z-
dc.date.available2021-12-15T12:20:16Z-
dc.date.issued2021-
dc.date.submitted2021-12-09T09:25:33Z-
dc.identifier.citationProceedings of the International Conference on 3D Immersion (IC3D), IEEE,-
dc.identifier.isbn9781665458306-
dc.identifier.issn2379-1772-
dc.identifier.urihttp://hdl.handle.net/1942/36209-
dc.description.abstractStatic light fields are an image-based technology that allow for the photorealistic representation of inanimate objects and scenes in virtual environments. As such, static light fields have application opportunities in heterogeneous domains, including education, cultural heritage and entertainment. This paper contributes the design, implementation and performance evaluation of a web-based static light field consumption system. The proposed system allows static light field datasets to be adaptively streamed over the network and then to be visualized in a vanilla web browser. The performance evaluation results prove that real-time consumption of static light fields at AR/VR-compatible framerates of 90 FPS or more is feasible on commercial off-the-shelf hardware. Given the ubiquitous availability of web browsers on modern consumption devices (PCs, smart TVs, Head Mounted Displays,. . .), our work is intended to significantly improve the accessibility and exploitation of static light field technology. The JavaScript client code is open-sourced to maximize our work's impact.-
dc.language.isoen-
dc.publisherIEEE-
dc.subject.otherJavaScript-
dc.subject.otherIndexedDB-
dc.subject.otherWebVR-
dc.subject.otherHTTP Adaptive Streaming-
dc.subject.otherMPEG-DASH-
dc.titleAdaptive Streaming and Rendering of Static Light Fields in the Web Browser-
dc.typeProceedings Paper-
local.bibliographicCitation.conferencedate08/12/2021-
local.bibliographicCitation.conferencenameInternational Conference on 3D Immersion (IC3D)-
local.bibliographicCitation.conferenceplaceBrussels, Belgium (online)-
dc.identifier.epage8-
dc.identifier.spage1-
local.format.pages8-
local.bibliographicCitation.jcatC1-
local.publisher.place345 E 47TH ST, NEW YORK, NY 10017 USA-
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[6] John Flynn, Michael Broxton, Paul Debevec, Matthew DuVall, Graham Fyffe, Ryan Overbeck, Noah Snavely, and Richard Tucker. Deepview: View synthesis with learned gradient descent. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2019. [7] Steven J. Gortler, Radek Grzeszczuk, Richard Szeliski, and Michael F. Cohen. The lumigraph. In Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’96, page 43–54, New York, NY, USA, 1996. Association for Computing Machinery. [8] GPU for the Web Community Group. WebGPU specification. https://gpuweb.github.io/gpuweb/, 2021. [9] Aaron Isaksen, Leonard McMillan, and Steven J. Gortler. Dynamically reparameterized light fields. In Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’00, page 297–306, USA, 2000. ACM Press/Addison-Wesley Publishing Co. [10] Péter Tamas Kovacs, Zsolt Nagy, Attila Barsi, Vamsi Kiran Adhikarla, and Robert Bregovic. Overview of the applicability of H.264/MVC for real-time light-field applications. In 2014 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTVCON), pages 1–4, 2014. [11] Péter Tamas Kovacs, Alireza Zare, Tibor Balogh, Robert Bregovic, and Atanas Gotchev. Architectures and Codecs for Real-Time Light Field Streaming. Journal of Imaging Science and Technology, 61(1):10403–1–10403–13, Jan 2017. [12] Akira Kubota, Aljoscha Smolic, Marcus Magnor, Masayuki Tanimoto, Tsuhan Chen, and Cha Zhang. Multiview imaging and 3DTV. IEEE Signal Processing Magazine, 24(6):10–21, 2007. [13] Elise Lachat, Helene Macher, Marie-Anne Mittet, Tiemo Landes, and Pierre Grussenmeyer. First Experiences With Kinect v2 Sensor for Close Range 3D Modelling. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-5/W4:93–100, 2015. [14] Marc Levoy and Pat Hanrahan. Light Field Rendering. In Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’96, pages 31–42, New York, NY, USA, 1996. ACM. [15] Shenhong Li, Xiongwu Xiao, Bingxuan Guo, and Lin Zhang. A Novel OpenMVS-Based Texture Reconstruction Method Based on the Fully Automatic Plane Segmentation for 3D Mesh Models. Remote Sensing, 12(23), 2020. [16] Steven Maesen, Patrik Goorts, and Philippe Bekaert. Omnidirectional free viewpoint video using panoramic light fields. In 2016 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), pages 1–4, 2016. [17] Leonard McMillan and Gary Bishop. Plenoptic modeling: An image-based rendering system. In Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’95, page 39–46, New York, NY, USA, 1995. Association for Computing Machinery. [18] Media Working Group. WebCodecs W3C Working Draft. https://www.w3.org/TR/webcodecs/, 2021. [19] Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng. NeRF: Representing scenes as neural radiance fields for view synthesis. In Proceedings of the 16th European Conference on Computer Vision, ECCV ’20, 2020. [20] Ryan S Overbeck, Daniel Erickson, Daniel Evangelakos, Matt Pharr, and Paul Debevec. A system for acquiring, processing, and rendering panoramic light field stills for virtual reality. ACM Transactions on Graphics (TOG), 37(6):1–15, 2018. [21] Iraj Sodagar. The MPEG-DASH Standard for Multimedia Streaming Over the Internet. IEEE MultiMedia, 18(4):62–67, April 2011. [22] Ruben Verhack, Thomas Sikora, Glenn Van Wallendael, and Peter Lambert. Steered Mixture-of-Experts for Light Field Images and Video: Representation and Coding. IEEE Transactions on Multimedia, 22(3):579–593, 2020. [23] Maarten Wijnants, Hendrik Lievens, Nick Michiels, Jeroen Put, Peter Quax, and Wim Lamotte. Standards-Compliant HTTP Adaptive Streaming of Static Light Fields. In Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology, VRST ’18, 2018.-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.identifier.doi10.1109/IC3D53758.2021.9687239-
dc.identifier.isi000782384400009-
local.provider.typePdf-
local.bibliographicCitation.btitleProceedings of the I2021 nternational Conference on 3D Immersion (IC3D)-
local.uhasselt.uhpubyes-
local.dataset.doihttps://doi.org/10.5281/zenodo.5734061-
local.dataset.doihttps://doi.org/10.5281/zenodo.5730526-
local.uhasselt.internationalno-
item.contributorLIEVENS, Hendrik-
item.contributorZOOMERS, Brent-
item.contributorWIJNANTS, Maarten-
item.contributorPUT, Jeroen-
item.contributorLAMOTTE, Wim-
item.contributorQUAX, Peter-
item.contributorMICHIELS, Nick-
item.fulltextWith Fulltext-
item.validationecoom 2023-
item.fullcitationLIEVENS, Hendrik; ZOOMERS, Brent; WIJNANTS, Maarten; PUT, Jeroen; LAMOTTE, Wim; QUAX, Peter & MICHIELS, Nick (2021) Adaptive Streaming and Rendering of Static Light Fields in the Web Browser. In: Proceedings of the International Conference on 3D Immersion (IC3D), IEEE,.-
item.accessRightsOpen Access-
Appears in Collections:Research publications
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