BMVC 2004, Kingston, 7th-9th Sept, 2004

Detection of Planar Regions with Uncalibrated Stereo using Distributions of Feature Points
Y. Kanazawa and H. Kawakami (Toyohashi University of Technology, Japan)

We propose a robust method for detecting local planar regions in a scene
with an uncalibrated stereo. Our method is based on random sampling using
distributions of feature point locations. For doing RANSAC, we use the distributions
for each feature point defined by the distances between the point
and the other points. We first choose a correspondence by using an uniform
distribution and next choose candidate correspondences by using the distribution
of the chosen point. Then, we compute a homography from the chosen
correspondences and find the largest consensus set of the homography. We
repeat this procedure until all regions are detected. We demonstrate that our
method is robust to the outliers in a scene by simulations and real image
(pdf article)