Facet matching from an uncalibrated pair of images
Since for recognition tasks it is known that planar invariants are more easily obtained than others, decomposing a scene in terms of planar parts becomes Very interresting. This paper presents a new approach to find the projections of planar surfaces in a pair of images. For this task we introduce the facet concept defined by linked edges (chains) and corners. We use collineations as projective information to match and verify their planarity. Our contribution consists in obtaining from an uncalibrated stereo pair of images a match of "planar" chains based an matched corners. Collineations are constrained by the fundamental matrix information and a Kalman filter approach is used to refine its computation.
planarity collineation kalman filter chain matching feature extraction