Temporally coherent 4D reconstruction of complex dynamic scenes
March 10, 2016 Β· Declared Dead Β· π Computer Vision and Pattern Recognition
"No code URL or promise found in abstract"
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Authors
Armin Mustafa, Hansung Kim, Jean-Yves Guillemaut, Adrian Hilton
arXiv ID
1603.03381
Category
cs.CV: Computer Vision
Citations
82
Venue
Computer Vision and Pattern Recognition
Last Checked
3 months ago
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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