Temporally coherent 4D reconstruction of complex dynamic scenes
Temporally coherent 4D reconstruction of complex dynamic scenes
This paper presents an approach for reconstruction of 4D temporally coherent models of complex dynamic scenes. No prior knowledge is required of scene structure or camera calibration allowing reconstruction from multiple moving cameras. Sparse-to-dense temporal correspondence is integrated with joint multi-view segmentation and reconstruction to obtain a complete 4D representation of static and dynamic objects. Temporal coherence is exploited to overcome visual ambiguities resulting in improved reconstruction of complex scenes. Robust joint segmentation and reconstruction of dynamic objects is achieved by introducing a geodesic star convexity constraint. Comparative evaluation is performed on a variety of unstructured indoor and outdoor dynamic scenes with hand-held cameras and multiple people. This demonstrates reconstruction of complete temporally coherent 4D scene models with improved nonrigid object segmentation and shape reconstruction.
4660-4669
Mustafa, Armin
29037014-ab45-4368-81e3-6b698e9bbbd0
Kim, Hansung
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Guillemaut, Jean-Yves
fcaefbd8-8ba1-4c43-978c-0b5d432a3285
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
12 December 2016
Mustafa, Armin
29037014-ab45-4368-81e3-6b698e9bbbd0
Kim, Hansung
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Guillemaut, Jean-Yves
fcaefbd8-8ba1-4c43-978c-0b5d432a3285
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
Mustafa, Armin, Kim, Hansung, Guillemaut, Jean-Yves and Hilton, Adrian
(2016)
Temporally coherent 4D reconstruction of complex dynamic scenes.
In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
IEEE.
.
(doi:10.1109/CVPR.2016.504).
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper presents an approach for reconstruction of 4D temporally coherent models of complex dynamic scenes. No prior knowledge is required of scene structure or camera calibration allowing reconstruction from multiple moving cameras. Sparse-to-dense temporal correspondence is integrated with joint multi-view segmentation and reconstruction to obtain a complete 4D representation of static and dynamic objects. Temporal coherence is exploited to overcome visual ambiguities resulting in improved reconstruction of complex scenes. Robust joint segmentation and reconstruction of dynamic objects is achieved by introducing a geodesic star convexity constraint. Comparative evaluation is performed on a variety of unstructured indoor and outdoor dynamic scenes with hand-held cameras and multiple people. This demonstrates reconstruction of complete temporally coherent 4D scene models with improved nonrigid object segmentation and shape reconstruction.
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More information
Accepted/In Press date: 1 April 2016
e-pub ahead of print date: 12 December 2016
Published date: 12 December 2016
Venue - Dates:
2016 IEEE Conference on Computer Vision and Pattern Recognition <br/>, , Las Vegas, United States, 2016-06-27 - 2016-06-30
Identifiers
Local EPrints ID: 438829
URI: http://eprints.soton.ac.uk/id/eprint/438829
ISSN: 1063-6919
PURE UUID: c0395184-65be-4c05-aaa5-43441b734b5f
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Date deposited: 25 Mar 2020 17:31
Last modified: 17 Mar 2024 04:01
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Contributors
Author:
Armin Mustafa
Author:
Hansung Kim
Author:
Jean-Yves Guillemaut
Author:
Adrian Hilton
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