Sequential scene parsing using range and intensity information

This paper describes an extension of the sequential scene analysis system presented by Hager and Wegbreit [12]. In contrast to the original system, which was limited to scenes consisting of geometric primitives, such as spheres, cuboids, and cylinders computed from range data, the extended system is capable of dealing with arbitrarily shaped objects computed from range and intensity images. An object model composed of a triangulated geometry and intensity-based SURF features is introduced. The integration of prior object models into the sequential scene parsing framework is described. The extended system is evaluated with respect to pose estimation and its ability to handle complex scene sequences. It is shown that the new object models enable accurate pose estimation and reliable recognition even in highly cluttered scenes.