posted on 2008-01-01, 00:00authored bySantosh K. Divvala, Alexei Efros, Martial Hebert
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 [3] 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.