Fast 3D Stabilization and Mosaic Construction
Abstract
The authors present a fast electronic image stabilization system that compensates for 3D rotation. The extended Kalman filter framework is employed to estimate the rotation between frames, which is represented using unit quaternions. A small set of automatically selected and tracked feature points are used as measurements. The effectiveness of this technique is also demonstrated by constructing mosaic images from the motion estimates, and comparing them to mosaics built from 2D stabilization algorithms. Two different stabilization schemes are presented. The first, implemented in a real-time platform based on a Datacube MV200 board, estimates the motion between two consecutive frames and is able to process gray level images of resolution 128/spl times/120 at 10 Hz. The second scheme estimates the motion between the current frame and an inverse mosaic; this allows better estimation without the need for indexing the new image frames. Experimental results for both schemes using real and synthetic image sequences are presented.
Cite
Text
Morimoto and Chellappa. "Fast 3D Stabilization and Mosaic Construction." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997. doi:10.1109/CVPR.1997.609396Markdown
[Morimoto and Chellappa. "Fast 3D Stabilization and Mosaic Construction." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997.](https://mlanthology.org/cvpr/1997/morimoto1997cvpr-fast/) doi:10.1109/CVPR.1997.609396BibTeX
@inproceedings{morimoto1997cvpr-fast,
title = {{Fast 3D Stabilization and Mosaic Construction}},
author = {Morimoto, Carlos and Chellappa, Rama},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1997},
pages = {660-665},
doi = {10.1109/CVPR.1997.609396},
url = {https://mlanthology.org/cvpr/1997/morimoto1997cvpr-fast/}
}