Segment-based detection of moving objects in a sequence of images

In this paper, we present a method to detect moving objects in a scene modelled as a set of line segments and using the measure of their 2D motion through a monocular sequence of images. These measures are supplied by a segment tracker using a Kalman filtering approach. In order to perform such a detection task, we have to determine and sort the rigid structures; we work with structures of five segments and declare that they are rigid if they verify several rigidity conditions. Using these constraints, we sort them into "classes" according to their associated 2D affine motion fields.