Segmentation of Moving Objects by Robust Motion Parameter Estimation over Multiple Frames
Abstract
A method for detecting and segmenting accurately moving objects in monocular image sequences is proposed. It consists of two modules, namely a motion estimation and a motion segmentation module. The motion estimation problem is formulated as a time varying motion parameter estimation over multiple frames. Robust regression techniques are used to estimate these parameters. The motion parameters for the different moving objects are obtained by successive estimations on regions for which the previously estimated motion parameters are not valid. The segmentation module combines all motion parameters and the gray level information in order to obtain the motion boundaries and to improve them by using time integration. Experimental results on real image sequences with static or moving camera in the presence of multiple moving objects are reported.
Cite
Text
Ayer et al. "Segmentation of Moving Objects by Robust Motion Parameter Estimation over Multiple Frames." European Conference on Computer Vision, 1994. doi:10.1007/BFB0028364Markdown
[Ayer et al. "Segmentation of Moving Objects by Robust Motion Parameter Estimation over Multiple Frames." European Conference on Computer Vision, 1994.](https://mlanthology.org/eccv/1994/ayer1994eccv-segmentation/) doi:10.1007/BFB0028364BibTeX
@inproceedings{ayer1994eccv-segmentation,
title = {{Segmentation of Moving Objects by Robust Motion Parameter Estimation over Multiple Frames}},
author = {Ayer, Serge and Schroeter, Philippe and Bigün, Josef},
booktitle = {European Conference on Computer Vision},
year = {1994},
pages = {316-327},
doi = {10.1007/BFB0028364},
url = {https://mlanthology.org/eccv/1994/ayer1994eccv-segmentation/}
}