Surface-based general 3D object detection and pose estimation

3D object detection and pose estimation often requires a 3D object model, and even so, it is a difficult problem if the object is heavily occluded in a cluttered scene. In this paper, we introduce a novel approach for recognizing and localizing 3D objects based on their appearances through segmentation of 3D surfaces. The approach can identify multiple occluded objects in a scene, which may include different instances of the same object, and estimate the pose of each entire object even if the object can only be seen partially due to occlusion.