University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Temporally coherent general dynamic scene reconstruction

Mustafa, Armin, Volino, Marco, Kim, Hansung, Guillemaut, Jean-Yves and Hilton, Adrian (2020) Temporally coherent general dynamic scene reconstruction International Journal of Computer Vision.

[img] Text
emporally Coherent General Dynamic Scene Reconstruction.pdf - Accepted version Manuscript
Restricted to Repository staff only until 5 August 2021.

Download (6MB)
[img]
Preview
Text
Mustafa2020_Article_TemporallyCoherentGeneralDynam.pdf - Version of Record
Available under License Creative Commons Attribution.

Download (7MB) | Preview

Abstract

Existing techniques for dynamic scene re- construction from multiple wide-baseline cameras pri- marily focus on reconstruction in controlled environ- ments, with fixed calibrated cameras and strong prior constraints. This paper introduces a general approach to obtain a 4D representation of complex dynamic scenes from multi-view wide-baseline static or moving cam- eras without prior knowledge of the scene structure, ap- pearance, or illumination. Contributions of the work are: An automatic method for initial coarse reconstruc- tion to initialize joint estimation; Sparse-to-dense tem- poral correspondence integrated with joint multi-view segmentation and reconstruction to introduce tempo- ral coherence; and a general robust approach for joint segmentation refinement and dense reconstruction of dynamic scenes by introducing shape constraint. Com- parison with state-of-the-art approaches on a variety of complex indoor and outdoor scenes, demonstrates im- proved accuracy in both multi-view segmentation and dense reconstruction. This paper demonstrates unsuper- vised reconstruction of complete temporally coherent 4D scene models with improved non-rigid object seg- mentation and shape reconstruction and its application to various applications such as free-view rendering and virtual reality.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Mustafa, Arminarmin.mustafa@surrey.ac.uk
Volino, Marcomarco.volino@surrey.ac.uk
Kim, HansungH.Kim@surrey.ac.uk
Guillemaut, Jean-YvesJ.Guillemaut@surrey.ac.uk
Hilton, AdrianA.Hilton@surrey.ac.uk
Date : 18 August 2020
Funders : Royal Academy of Engineering Research Fellowship, EPSRC
DOI : 10.1007/s11263-020-01367-2
Grant Title : Royal Academy of Engineering Research Fellowship
Copyright Disclaimer : © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Uncontrolled Keywords : Dynamic 4D reconstruction, Segmentation
Additional Information : Embargo OK Metadata OK No Further Action
Depositing User : James Marshall
Date Deposited : 26 Aug 2020 14:10
Last Modified : 26 Aug 2020 16:52
URI: http://epubs.surrey.ac.uk/id/eprint/858511

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800