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Can Similar Scenes help Surface Layout Estimation?

Santosh Kumar Divvala, Alexei A. Efros and Martial Hebert
Carnegie Mellon University, IEEE Workshop on Internet Vision, at CVPR'08, June, 2008

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We describe a preliminary investigation of utilising large amounts of unlabelled image data to help in the estimation of rough scene layout. We take the single-view geometry estimation system of Hoiem et al~cite{Hoiem_ijcv07} as the baseline and see if it is possible to improve its performance by considering a set of similar scenes gathered from the web. The two complimentary approaches being considered are 1) improving surface classification by using average geometry estimated from the matches, and 2) improving surface segmentation by injecting segments generated from the average of the matched images. The system is evaluated using the labelled 300-image dataset of Hoiem et al. and shows promising results.

BibTeX Reference
title = {Can Similar Scenes help Surface Layout Estimation?},
author = {Santosh Kumar Divvala and Alexei A. Efros and Martial Hebert},
booktitle = {IEEE Workshop on Internet Vision, at CVPR'08},
school = {Robotics Institute , Carnegie Mellon University},
month = {June},
year = {2008},
address = {Pittsburgh, PA},