A projective framework for scene segmentation in the presence of moving objects

Given a sequence of pairs of images gathered with an uncalibrated stereo camera pair and given a set of point-to-point correspondences between, these image pairs, we describe a method that segments the observed scene into static and moving objects while it rejects badly matched points. Unlike many approaches which were suggested in the past, the method allows for both motion of the camera pair (egomotion) and non rigid scenes (scenes composed of static objects as well as objects undergoing various motions). First we establish the projective framework enabling us to characterize rigid motion in projective space. Second we use this characterization in conjunction with a robust estimation technique to determine egomotion. Third we describe a method based on data classification which further considers the non-static scene points anal groups them into several moving objects. Finally we show some preliminary experiments involving a moving stereo head observing both static and moving objects