Differential Epipolar Constraint in Mobile Robot Egomotion Estimation
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The detection of moving objects is crucial for robot navigation and driver assistance systems. In this paper the detectability of moving objects is studied. To this end, image correspondences over two and three frames are considered whereas the images are acquired by a moving monocular camera. The detection is based on the constraints linked to static 3D points. These constraints (epipolar, positive depth, positive height, and trifocal constraint) are discussed briefly, and an algorithm incorporating all of them is proposed. The individual constraints differ in their action depending on the motion of the object. Thus, the detectability of a moving object is influenced by its motion. Three types of motions are investigated: parallel, lateral, and circular motion. The study of the detection limits is applied to real imagery.