3D Model Acquisition from Monocular Image Sequences
Abstract
Automatic building 3D models of objects and scenes from a sequence of 2D monocular images is approached by first building a partial model (possibly noisy) and then extending and refining it. The initial model is built by tracking and reconstructing shallow structures over a sequence of images using the constraint of affine trackability. This model is subsequently used to compute the pose that relates the model coordinate system and the camera coordinate system of the image frames in the sequence. The unmodeled 3D features (those not recovered by the shallow structure reconstruction) are tracked over the image sequence and their 3D locations recovered by a pseudotriangulation process. The triangulation process is also used to make new 3D measurements of the initial model points. These measurements are then fused with the previous estimates to refine the set of initial model points.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Kumar et al. "3D Model Acquisition from Monocular Image Sequences." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992. doi:10.1109/CVPR.1992.223273Markdown
[Kumar et al. "3D Model Acquisition from Monocular Image Sequences." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992.](https://mlanthology.org/cvpr/1992/kumar1992cvpr-d/) doi:10.1109/CVPR.1992.223273BibTeX
@inproceedings{kumar1992cvpr-d,
title = {{3D Model Acquisition from Monocular Image Sequences}},
author = {Kumar, Rakesh and Sawhney, Harpreet S. and Hanson, Allen R.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1992},
pages = {209-215},
doi = {10.1109/CVPR.1992.223273},
url = {https://mlanthology.org/cvpr/1992/kumar1992cvpr-d/}
}