TY  - CONF
AU  - Diego Cheda
AU  - Daniel Ponsa
AU  - Antonio Lopez
A2  - VISAPP
PY  - 2012//
TI  - Monocular Depth-based Background Estimation
BT  - 7th International Conference on Computer Vision Theory and Applications
SP  - 323
EP  - 328
N2  - 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.
UR  - http://www.experts.scival.com/uabcei/pubDetail.asp?t=pm&id=84862142155&o_id=29
L1  - http://refbase.cvc.uab.es/files/cpl2012e.pdf
N1  - ADAS
ID  - Diego Cheda2012
ER  -