Identification and pose under severe occlusion in range images

Object recognition may be a hard computer vision task under severe occlusion circumstances. This problem is efficiently solved in this paper through a new 3D recognition method for free-form objects. The technique uses the Depth Gradient Image Based on Silhouette representation (DGI-BS) and settles the problem of identification-pose under occlusion and noise requirements. DGI-BS synthesizes both surface and contour information of an object avoiding restrictions concerning the layout and visibility. Object recognition is carried out by means of a simple matching algorithm in the DGI-BS space which yields a point-to-point correspondence between scene and model. The method has been successfully tested in real scenes under occlusion and noise circumstances.