A model driven 3D image interpretation system applied to person detection in video images

Detecting persons in images is up to now an unsolved problem in general. We propose an approach which strictly follows the assumption that only objects and parts of these objects can be detected, if their appearance is known in advance. We consider the detection step as a first step towards the recognition process. The latter contains the reasoning about the movements of a person. The appearance of a 3D object means the description of the mapping of object features into the image. The proposed system uses a hierarchical model to control the image segmentation and matching process. It is a multipurpose model for articulated objects which is supporting the linkage of different features.