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Improving Free-Viewpoint Video Content Production Using RGB-Camera-Based Skeletal Tracking

MacQuarrie, A; Steed, A; (2020) Improving Free-Viewpoint Video Content Production Using RGB-Camera-Based Skeletal Tracking. In: 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). (pp. pp. 775-776). IEEE: Atlanta, GA, USA. Green open access

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Abstract

Free-Viewpoint Video (FVV) is a type of volumetric content in which an animated, video-textured 3D mesh of a character performance is constructed using data from an array of cameras. Previous work has demonstrated excellent results when creating motion graphs from FVV content, but these techniques are often prohibitively expensive in practice. We propose the use of skeletons to identify cut points between FVV clips, allowing a minimal set of frames to be processed into a 3D mesh. While our method performed with 2.8% poorer accuracy than the state-of-the-art for our synthetic dataset, cost and processing time requirements are dramatically reduced.

Type: Proceedings paper
Title: Improving Free-Viewpoint Video Content Production Using RGB-Camera-Based Skeletal Tracking
Event: 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)
ISBN-13: 9781728165325
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/VRW50115.2020.00238
Publisher version: https://doi.org/10.1109/VRW50115.2020.00238
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Virtual reality; Motion capture; Motion processing
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10100129
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