Segmentation and 2D Motion Estimation by Region Fragments
Abstract
A central problem in estimating multiple image motions is that 2-D motion estimation and region segmentation are mutually dependent. The authors present a new region description method for dealing with this mutual dependence problem. Segmentation and motion estimation are simultaneously performed by a clustering process based on color, motion, and pixel position. As a result of the clustering, an image is decomposed into region fragments. Each fragment is characterized by distribution parameters of color, pixel positions, and spatiotemporal intensity gradients. The image is described by the parameters of the region fragments; 2-D motion vectors for each fragment are obtained from the distribution parameters of the intensity gradients. By combining those features in the clustering process, regions are segmented more precisely, motion boundaries are not blurred, and the 2-D motions are obtained even in noisy areas. Experimental results are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Etoh and Shirai. "Segmentation and 2D Motion Estimation by Region Fragments." IEEE/CVF International Conference on Computer Vision, 1993. doi:10.1109/ICCV.1993.378220Markdown
[Etoh and Shirai. "Segmentation and 2D Motion Estimation by Region Fragments." IEEE/CVF International Conference on Computer Vision, 1993.](https://mlanthology.org/iccv/1993/etoh1993iccv-segmentation/) doi:10.1109/ICCV.1993.378220BibTeX
@inproceedings{etoh1993iccv-segmentation,
title = {{Segmentation and 2D Motion Estimation by Region Fragments}},
author = {Etoh, Minoru and Shirai, Yoshiaki},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1993},
pages = {192-199},
doi = {10.1109/ICCV.1993.378220},
url = {https://mlanthology.org/iccv/1993/etoh1993iccv-segmentation/}
}