In this paper, augmented reality techniques are used in order to create a virtual mirror for the real-time visualization of customized sports shoes. Similar to looking into a mirror when trying on new shoes in a shop, we create the same impression but for virtual shoes that the customer can design individually. For that purpose, we replace the real mirror by a large display that shows the mirrored input of a camera capturing the legs and shoes of a person. 3-D tracking of both feet and exchanging the real shoes by computer graphics models gives the impression of actually wearing the virtual shoes. The 3-D motion tracker presented in this paper, exploits mainly silhouette information to achieve robust estimates for both shoes from a single camera view. The use of a hierarchical approach in an image pyramid enables real-time estimation at frame rates of more than 30 frames per second.

In this paper, we present a system that enhances the visualization of customized sports shoes using augmented reality techniques. Instead of viewing yourself in a real mirror, sophisticated 3D image processing techniques are used to verify the appearance of new shoe models. A single camera captures the person and outputs the mirrored images onto a large display which replaces the real mirror. The 3D motion of both feet are tracked in real-time with a new motion tracking algorithm. Computer graphics models of the shoes are augmented into the video such that the person seems to wear the virtual shoes.

In this work, we present a framework to capture 3D models of faces in high resolutions with low computational load. The system captures only two pictures of the face, one illuminated with a colored stripe pattern and one with regular white light. The former is needed for the depth calculation, the latter is used as texture. Having these two images a combination of specialized algorithms is applied to generate a 3D model. The results are shown in different views: simple surface, wire grid respective polygon mesh or textured 3D surface.

We present our system for the capturing and analysis of 3D facial motion. A high speed camera is used as capture unit in combination with two surface mirrors. The mirrors provide two additional virtual views of the face without the need of multiple cameras and to avoid synchronization problems. We use this system to capture the motion of a person's face while speaking. Investigations of these facial motions are presented and rigid and non-rigid motion are analyzed. In order to extract only facial deformation independent from head pose, we use a new and simple approach for separating rigid and non-rigid motion named weight-compensated motion estimation (WCME). This approach weights the data points according to their influence to the desired motion model. We also present first results of our model-based facial deformation analysis. Such results can be used for facial animations in order to achieve a higher degree of quality.

In this paper, we present an image-based method for the tracking and rendering of faces. We use the algorithm in an immersive video conferencing system where multiple participants are placed at a virtual table. This requires viewpoint modification of dynamic objects. Since hair and uncovered areas are difficult to model by pure 3-D geometry-based warping, we add image-based rendering techniques to the system. By interpolating novel views from a 3-D image volume, natural looking results can be achieved. The image-based component is embedded into a geometry-based approach that models temporally changing facial features. Both geometry and image cube information are jointly exploited in facial expression analysis and synthesis.