Physics-based object pose and shape estimation from multiple views

This paper presents a new algorithm for object pose and shape estimation from multiple views. Using a qualitative shape recovery scheme the authors first segment the image into parts which belong to a vocabulary of primitives. Based on the additional constraints provided by the qualitative shapes the authors extend their physics-based framework to allow object pose and shape estimation from stereo images where the two cameras have arbitrary relative orientations. The authors then generalize their algorithm to integrate measurements from multiple views. To recover more complex objects the authors generalize the definition for the global bending deformation. The authors also present an algorithm for model discretization which evenly tessellates the model surface. The authors demonstrate the usefulness of their technique in experiments involving real images from of a variety of object shapes which may be partially occluded