Progressive 3D Model Acquisition with a Commodity Hand-Held Camera
Abstract
We present a system for progressive 3D model acquisition with a commodity hand-held camera. The pipeline starts with a real-time scanning stage accomplished using a sparse point-based tracker for camera pose estimation and a dense patch-based tracker for dense reconstruction. While the user scans the target object, a model composed of local planar patches is continuously updated and displayed for visual feedback. This live feedback loop allows the user to choose new viewpoints based on the state of the current reconstruction, and determine if the model is completely covered in desired details. After live scanning is completed, our system refines the reconstructed patches into denser and more accurate patches through an offline model refinement procedure. We demonstrate the ability of our system on various real datasets.
Cite
Text
Kang and Medioni. "Progressive 3D Model Acquisition with a Commodity Hand-Held Camera." IEEE/CVF Winter Conference on Applications of Computer Vision, 2015. doi:10.1109/WACV.2015.43Markdown
[Kang and Medioni. "Progressive 3D Model Acquisition with a Commodity Hand-Held Camera." IEEE/CVF Winter Conference on Applications of Computer Vision, 2015.](https://mlanthology.org/wacv/2015/kang2015wacv-progressive/) doi:10.1109/WACV.2015.43BibTeX
@inproceedings{kang2015wacv-progressive,
title = {{Progressive 3D Model Acquisition with a Commodity Hand-Held Camera}},
author = {Kang, Zhuoliang and Medioni, Gérard G.},
booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision},
year = {2015},
pages = {270-277},
doi = {10.1109/WACV.2015.43},
url = {https://mlanthology.org/wacv/2015/kang2015wacv-progressive/}
}