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Authors: Diego Cheda ; Daniel Ponsa and Antonio M. López

Affiliation: Universitat Autònoma de Barcelona, Spain

Keyword(s): Background Estimation, Depth Estimation, Energy Minimization, Graph Cuts.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Image Enhancement and Restoration ; Image Formation and Preprocessing ; Segmentation and Grouping

Abstract: In this paper, we address the problem of reconstructing the background of a scene from a video sequence with occluding objects. The images are taken by hand-held cameras. Our method composes the background by selecting the appropriate pixels from previously aligned input images. To do that, we minimize a cost function that penalizes the deviations from the following assumptions: background represents objects whose distance to the camera is maximal, and background objects are stationary. Distance information is roughly obtained by a supervised learning approach that allows us to distinguish between close and distant image regions. Moving foreground objects are filtered out by using stationariness and motion boundary constancy measurements. The cost function is minimized by a graph cuts method. We demonstrate the applicability of our approach to recover an occlusion-free background in a set of sequences.

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Paper citation in several formats:
Cheda, D.; Ponsa, D. and M. López, A. (2012). MONOCULAR DEPTH-BASED BACKGROUND ESTIMATION. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP; ISBN 978-989-8565-03-7; ISSN 2184-4321, SciTePress, pages 323-328. DOI: 10.5220/0003816503230328

@conference{visapp12,
author={Diego Cheda. and Daniel Ponsa. and Antonio {M. López}.},
title={MONOCULAR DEPTH-BASED BACKGROUND ESTIMATION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP},
year={2012},
pages={323-328},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003816503230328},
isbn={978-989-8565-03-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP
TI - MONOCULAR DEPTH-BASED BACKGROUND ESTIMATION
SN - 978-989-8565-03-7
IS - 2184-4321
AU - Cheda, D.
AU - Ponsa, D.
AU - M. López, A.
PY - 2012
SP - 323
EP - 328
DO - 10.5220/0003816503230328
PB - SciTePress