A NEURAL NETWORK APPROACH TO BAYESIAN BACKGROUND MODELING FOR VIDEO OBJECT SEGMENTATION
Dubravko Culibrk, Oge Marques, Daniel Socek, Hari Kalva, Borko Furht
2006
Abstract
Object segmentation from a video stream is an essential task in video processing and forms the foundation of scene understanding, object-based video encoding (e.g. MPEG4), and various surveillance and2D-to-pseudo-3D conversion applications. The task is difficult and exacerbated by the advances in video capture and storage. Increased resolution of the sequences requires development of new, more efficient algorithms for object detection and segmentation. The paper presents a novel neural network based approach to background modeling for motion based object segmentation in video sequences. The proposed approach is designed to enable efficient, highly-parallelized hardware implementation. Such a system would be able to achieve real time segmentation of high-resolution sequences.
DownloadPaper Citation
in Harvard Style
Culibrk D., Marques O., Socek D., Kalva H. and Furht B. (2006). A NEURAL NETWORK APPROACH TO BAYESIAN BACKGROUND MODELING FOR VIDEO OBJECT SEGMENTATION . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 474-479. DOI: 10.5220/0001374604740479
in Bibtex Style
@conference{visapp06,
author={Dubravko Culibrk and Oge Marques and Daniel Socek and Hari Kalva and Borko Furht},
title={A NEURAL NETWORK APPROACH TO BAYESIAN BACKGROUND MODELING FOR VIDEO OBJECT SEGMENTATION},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={474-479},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001374604740479},
isbn={972-8865-40-6},
}
in EndNote Style
TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - A NEURAL NETWORK APPROACH TO BAYESIAN BACKGROUND MODELING FOR VIDEO OBJECT SEGMENTATION
SN - 972-8865-40-6
AU - Culibrk D.
AU - Marques O.
AU - Socek D.
AU - Kalva H.
AU - Furht B.
PY - 2006
SP - 474
EP - 479
DO - 10.5220/0001374604740479