Active Object Recognition Using Appearance-based Representations Derived from Solid Geometric Models

We present new test results for our active object recognition algorithms. The algorithms are used to classify and estimate the pose of objects in di erent stable rest positions and automatically re-position the camera if the class or pose of an object is ambiguous in a given image. Multiple object views are now used in determining both the nal object class and pose estimate; previously, multiple views were used for classi cation only. A feature space trajectory (FST) in eigenspace is used to represent 3-D distorted views of an object. FSTs are constructed using images rendered from solid models. We discuss lighting and material settings for photorealism in the rendering process. The FSTs are analyzed to determine the camera positions that best resolve ambiguities. Real objects are recognized from intensity images using the FST representation derived from rendered imagery.