3D Model Search and Pose Estimation from Single Images Using VIP Features
Abstract
This paper describes a method to efficiently search for 3D models in a city-scale database and to compute the camera poses from single query images. The proposed method matches SIFT features (from a single image) to viewpoint invariant patches (VIP) from a 3D model by warping the SIFT features approximately into the orthographic frame of the VIP features. This significantly increases the number of feature correspondences which results in a reliable and robust pose estimation. We also present a 3D model search tool that uses a visual word based search scheme to efficiently retrieve 3D models from large databases using individual query images. Together the 3D model search and the pose estimation represent a highly scalable and efficient city-scale localization system. The performance of the 3D model search and pose estimation is demonstrated on urban image data.
Cite
Text
Wu et al. "3D Model Search and Pose Estimation from Single Images Using VIP Features." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4563037Markdown
[Wu et al. "3D Model Search and Pose Estimation from Single Images Using VIP Features." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/wu2008cvprw-3d/) doi:10.1109/CVPRW.2008.4563037BibTeX
@inproceedings{wu2008cvprw-3d,
title = {{3D Model Search and Pose Estimation from Single Images Using VIP Features}},
author = {Wu, Changchang and Fraundorfer, Friedrich and Frahm, Jan-Michael and Pollefeys, Marc},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2008},
pages = {1-8},
doi = {10.1109/CVPRW.2008.4563037},
url = {https://mlanthology.org/cvprw/2008/wu2008cvprw-3d/}
}