3D pose estimation and shape coding of moving objects based on statistical morphological skeleton

Recognition-based tracking and image coding methods are often based on different techniques. However, these techniques share the necessity of reliable and fast methods for the representation of the information content of the scene. In this paper, a method based on a lossy shape descriptor is presented which can be used for both recognition and coding purposes. Statistical Morphological Skeleton provides a noise-robust shape descriptor on which a further approximation phase is performed in order to improve the compression ratio. Then, it is possible to estimate the object's pose through a comparison of the shape descriptor with a set of object models stored in a database. An application to surveillance is presented where the obtained description is used to transmit shape information to a remote control center.