3-D Motion and Structure from 2-D Motion Causally Integrated over Time: Implementation
Abstract
The causal estimation of three-dimensional motion from a sequence of two-dimensional images can be posed as a nonlinear filtering problem. We describe the implementation of an algorithm whose uniform observability, minimal realization and stability have been proven analytically in [ 5 ]. We discuss a scheme for handling occlusions, drift in the scale factor and tuning of the filter. We also present an extension to partially calibrated camera models and prove its observability. We report the performance of our implementation on a few long sequences of real images. More importantly, however, we have made our real-time implementation - which runs on a personal computer - available to the public for first-hand testing.
Cite
Text
Chiuso et al. "3-D Motion and Structure from 2-D Motion Causally Integrated over Time: Implementation." European Conference on Computer Vision, 2000. doi:10.1007/3-540-45053-X_47Markdown
[Chiuso et al. "3-D Motion and Structure from 2-D Motion Causally Integrated over Time: Implementation." European Conference on Computer Vision, 2000.](https://mlanthology.org/eccv/2000/chiuso2000eccv-d/) doi:10.1007/3-540-45053-X_47BibTeX
@inproceedings{chiuso2000eccv-d,
title = {{3-D Motion and Structure from 2-D Motion Causally Integrated over Time: Implementation}},
author = {Chiuso, Alessandro and Favaro, Paolo and Jin, Hailin and Soatto, Stefano},
booktitle = {European Conference on Computer Vision},
year = {2000},
pages = {734-750},
doi = {10.1007/3-540-45053-X_47},
url = {https://mlanthology.org/eccv/2000/chiuso2000eccv-d/}
}