Title
Accurate 3D Reconstruction of Dynamic Scenes from Monocular Image Sequences with Severe Occlusions
Abstract
The paper introduces an accurate solution to dense orthographic Non-Rigid Structure from Motion (NRSfM) in scenarios with severe occlusions or, likewise, inaccurate correspondences. We integrate a shape prior term into variational optimisation framework. It allows to penalize irregularities of the time-varying structure on the per-pixel level if correspondence quality indicator such as an occlusion tensor is available. We make a realistic assumption that several non-occluded views of the scene are sufficient to estimate an initial shape prior, though the entire observed scene may exhibit non-rigid deformations. Experiments on synthetic and real image data show that the proposed framework significantly outperforms state of the art methods for correspondence establishment in combination with the state of the art NRSfM methods. Together with the profound insights into optimisation methods, implementation details for heterogeneous platforms are provided.
Year
DOI
Venue
2017
10.1109/WACV.2017.38
2017 IEEE Winter Conference on Applications of Computer Vision (WACV)
Keywords
DocType
Volume
dynamic scene 3D reconstruction,monocular image sequences,severe-occlusions,dense orthographic nonrigid structure-from-motion,shape prior term,variational optimisation framework,irregularity penalization,time-varying structure,quality indicator,nonoccluded views,nonrigid deformations,synthetic image data,real image data,NRSfM methods,heterogeneous platforms
Journal
abs/1712.07472
ISSN
ISBN
Citations 
2472-6737
978-1-5090-4823-6
2
PageRank 
References 
Authors
0.36
41
3
Name
Order
Citations
PageRank
Vladislav Golyanik12212.55
Torben Fetzer220.70
Didier Stricker31266138.03