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NonLinear Refinement of Structure from Motion Reconstruction by Taking Advantage of a Partial Knowledge of the Environment

Mohamed Tamaazousti, Vincent Gay-Bellile, Sylvie Naudet-Collette, Steve Bourgeois, Michel Dhome
CVPR 2011 pp. 3073-3080
doi:10.1109/CVPR.2011.5995358 /cvpr/2011/tamaazousti2011cvpr-nonlinear/

Abstract

We address the challenging issue of camera localization in a partially known environment, i.e. for which a geometric 3D model that covers only a part of the observed scene is available. When this scene is static, both known and unknown parts of the environment provide constraints on the camera motion. This paper proposes a nonlinear refinement process of an initial SfM reconstruction that takes advantage of these two types of constraints. Compare to those that exploit only the model constraints i.e. the known part of the scene, including the unknown part of the environment in the optimization process yields a faster, more accurate and robust refinement. It also presents a much larger convergence basin. This paper will demonstrate these statements on varied synthetic and real sequences for both 3D object tracking and outdoor localization applications.

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Cite

Text

Tamaazousti et al. "NonLinear Refinement of Structure from Motion Reconstruction by Taking Advantage of a Partial Knowledge of the Environment." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011. doi:10.1109/CVPR.2011.5995358

Markdown

[Tamaazousti et al. "NonLinear Refinement of Structure from Motion Reconstruction by Taking Advantage of a Partial Knowledge of the Environment." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011.](https://mlanthology.org/cvpr/2011/tamaazousti2011cvpr-nonlinear/) doi:10.1109/CVPR.2011.5995358

BibTeX

@inproceedings{tamaazousti2011cvpr-nonlinear,
  title     = {{NonLinear Refinement of Structure from Motion Reconstruction by Taking Advantage of a Partial Knowledge of the Environment}},
  author    = {Tamaazousti, Mohamed and Gay-Bellile, Vincent and Naudet-Collette, Sylvie and Bourgeois, Steve and Dhome, Michel},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2011},
  pages     = {3073-3080},
  doi       = {10.1109/CVPR.2011.5995358},
  url       = {https://mlanthology.org/cvpr/2011/tamaazousti2011cvpr-nonlinear/}
}