Direct Identification of Moving Objects and Background from 2D Motion Models
Abstract
This paper presents the dynamic scene analysis part of an original and consistent framework to video partitioning into shots, camera motion estimation and multiple motion analysis with a view to content-based video indexing. All the information parts required to achieve these different goals result from handling the apparent motion within consecutive image pairs. Within each extracted shot, a binary segmentation of the image is performed into regions whose motion either conforms or not to the 2D estimated dominant motion represented by a quadratic motion model. This paper focuses on a low-cost method based on projective geometry criteria to distinguish non-conforming regions generated by really moving objects from static ones in the scene. The proposed algorithm is validated on a variety of real image sequences.
Cite
Text
Csurka and Bouthemy. "Direct Identification of Moving Objects and Background from 2D Motion Models." IEEE/CVF International Conference on Computer Vision, 1999. doi:10.1109/ICCV.1999.791274Markdown
[Csurka and Bouthemy. "Direct Identification of Moving Objects and Background from 2D Motion Models." IEEE/CVF International Conference on Computer Vision, 1999.](https://mlanthology.org/iccv/1999/csurka1999iccv-direct/) doi:10.1109/ICCV.1999.791274BibTeX
@inproceedings{csurka1999iccv-direct,
title = {{Direct Identification of Moving Objects and Background from 2D Motion Models}},
author = {Csurka, Gabriela and Bouthemy, Patrick},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1999},
pages = {566-571},
doi = {10.1109/ICCV.1999.791274},
url = {https://mlanthology.org/iccv/1999/csurka1999iccv-direct/}
}