Object and pose recognition using contour and shape information

Object recognition and pose estimation are of significant importance for robotic visual servoing, manipulation and grasping tasks. Traditionally, contour and shape based methods have been considered as most adequate for estimating stable and feasible grasps (Bicchi and Kumar, 2000). A new research direction has been advocated in visual servoing where image moments are used to define a suitable error function to be minimized. Compared to appearance based methods, contour and shape based approaches are also suitable for use with range sensors such as, for example, lasers. In this paper, we evaluate a contour based object recognition system building on the method in Nelson and Selinger (1998), suitable for objects of uniform color properties such as cups, cutlery, fruits etc. This system is one of the building blocks of a more complex object recognition system based both on stereo and appearance cues, (Bjorkman and Kragic, 2004). The system has a significant potential both in terms of service robot and programming by demonstration tasks. Experimental evaluation shows promising results in terms of robustness to occlusion and noise