Autonomous Tracking For Volumetric Video Sequences
Citation:
Moynihan, M., Ruano, S., Pagés, R., Smolic, A., Autonomous Tracking For Volumetric Video Sequences, Winter Conference on Applications of Computer Vision 2021 ( Online WACV January 5-9), Waikoloa, United StatesDownload Item:
Abstract:
As a rapidly growing medium, volumetric video is gaining attention beyond academia, reaching industry and creative communities alike. This brings new challenges to reduce the barrier to entry from a technical and economical point of view. We present a system for robustly and autonomously performing temporally coherent tracking for volumetric sequences, specifically targeting those from sparse setups or with noisy output. Our system will detect and recover missing pertinent geometry across highly incoherent sequences as well as provide users the option of propagating drastic topology edits. In this way, afford-able multi-view setups can leverage temporal consistency to reduce processing and compression overheads while also generating more aesthetically pleasing volumetric sequences.
Sponsor
Grant Number
Science Foundation Ireland (SFI)
15/RP/2776
Author's Homepage:
http://people.tcd.ie/smolica
Author: Smolic, Aljosa
Sponsor:
Science Foundation Ireland (SFI)Other Titles:
Winter Conference on Applications of Computer Vision 2021 (WACV 2021), 2021.Type of material:
Conference PaperCollections
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Full text availableSubject (TCD):
Creative Technologies , Digital Engagement , Digital Humanities , Computer Education/Literacy , Data Analysis , Image Processing , Information technology in education , Multimedia & CreativityDOI:
10.13140/RG.2.2.19803.59687Metadata
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