In this paper an object recognition and tracking approach for the mobile, marker-less and PDA-based augmented reality system AR-PDA is described. For object recognition and localization 2D features are extracted from images and compared with a priori known 3D models. The system consists of a 2D graph matching, 3D hypothesis generation and validation and an additional texture based validation step.

This paper presents VisiTrack, a novel approach for video based incremental tracking in real time. The major objectives in the development of VisiTrack was to design or select algorithms that are well suited for embedded real time computation. We had a special focus on latency reduction and storage minimization since the algorithms should run on mobile devices like PDAs with the appropriate extension, i.e. mainly a camera, in real time. The image analysis, position localization and error minimization of VisiTrack are explained in detail. For the image analysis algorithms of VisiTrack two major principles, linear processing and incremental concurrency, were defined and applied in order to fulfill real time constraints and reduce system latency. In order to meet real time requirements the position localization is based on a linear transformation between 3D world coordinates and 2D image coordinates. Afterwards a real time error minimization based on the Kalman filter is applied successfully. VisiTrack is applied in the Augmented Reality domain and in the field of robotic self localization.

This paper presents a model for real-time computer vision applications based on the synchronous dataflow (SDF) methodology. To accomplish the needs of computer vision applications (mainly access to pixel neighborhood and access to previous video frames) a new buffer concept called Structured Buffers replaces the FIFO buffers used in the SDF model. The model minimizes the system's latency and memory consumption and allows an execution time analysis which is an essential prerequisite for real-time applications. Finally a line-based edge vectorization is presented as an example of the usage of the presented model.