Shape Estimation of Transparent Objects by Using Inverse Polarization Ray Tracing
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The perception of transparent objects from images is knownto be a very hard problem in vision. Given a single image,it is difficult to even detect the presence of transparent objectsin the scene. In this paper, we explore what can be saidabout transparent objects by a moving observer. We showhow features that are imaged through a transparent objectbehave differently from those that are rigidly attached to thescene. We present a novel model-based approach to recoverthe shapes and the poses of transparent objects from knownmotion. The objects can be complex in that they may be composedof multiple layers with different refractive indices. Wehave conducted numerous simulations to verify the practicalfeasibility of our algorithm. We have applied it to real scenesthat include transparent objects and recovered the shapes ofthe objects with high accuracy.