In this paper, a novel Depth Image-based Rendering (DIBR) method, which generates virtual views from a video sequence and its associated Depth Maps (DMs), is presented. The proposed approach is especially designed to close holes in extrapolation scenarios, where only one original camera is available or the virtual view is placed outside the range of a set of original cameras. In such scenarios, large image regions become uncovered in the virtual view and need to be filled in a visually pleasing way. In order to handle such disocclussions, a depth preprocessing method is proposed, which is applied prior to 3-D image warping. As a first step, adaptive cross-trilateral median filtering is used to align depth discontinuities in the DM to color discontinuities in the textured image and to further reduce estimation errors in the DM. Then, a temporally consistent and adaptive asymmetric smoothing filter is designed and subsequently applied to the DM. The filter is adaptively weighted in such a way that only the DM regions that may reveal uncovered areas are filtered. Thus, strong distortions in other parts of the virtual textured image are prevented. By smoothing the depth map image, objects are slightly distorted and disocclusions in the virtual view are completely or partially covered. The proposed method shows considerable objective and subjective gains compared to the state-of-the-art one.

This paper gives an overview of the state-of-the-art in 3-D video postproduction and processing as well as an outlook to remaining challenges and opportunities. First, fundamentals of stereography are outlined that set the rules for proper 3-D content creation. Manipulation of the depth composition of a given stereo pair via view synthesis is identified as the key functionality in this context. Basic algorithms are described to adapt and correct fundamental stereo properties such as geometric distortions, color alignment, and stereo geometry. Then, depth image-based rendering is explained as the widely applied solution for view synthesis in 3-D content creation today. Recent improvements of depth estimation already provide very good results. However, in most cases, still interactive workflows dominate. Warping-based methods may become an alternative for some applications in the future, which do not rely on dense and accurate depth estimation. Finally, 2-D to 3-D conversion is covered, which is an important special area for reuse of existing legacy 2-D content in 3-D. Here various advanced algorithms are combined in interactive workflows.

The paper discusses an assistance system for stereo shooting and 3D production, called Stereoscopic Analyzer (STAN). A feature-based scene analysis estimates in real-time the relative pose of the two cameras in order to allow optimal camera alignment and lens settings directly at the set. It automatically eliminates undesired vertical disparities and geometrical distortions through image rectification. In addition, it detects the position of near- and far objects in the scene to derive the optimal inter-axial distance (stereo baseline), and gives a framing alert in case of stereoscopic window violation. Against this background the paper describes the system architecture, explains the theoretical background and discusses future developments.

The paper discusses an advanced approach for 3DTV services that is based on the concept of an N× video-plus-depth data representation. It particularly considers aspects of interoperability, scalability, and adaptability for the case that different multi-baseline geometries are used for multi-view capturing and 3D reproduction. In addition, it presents a method for the creation of depth maps and an algorithm for depth-image-based rendering related to the system approach.

Interoperability, scalability and adaptability are important features for a successful introduction of future 3D TV services. Hence, new concepts must be able to adapt the multi-view geometry of the capturing system to the geometry of the 3D reproduction systems. An approach is discussed, which considers these adaptation issues based on the concept of an Ntimesvideo-plus-depth data representation. The core algorithms for depth map creation on the analysis side and depth image based rendering on the reproduction side are presented

This paper describes an approach for creating high-resolution video panoramas of large-scale sport events. In an exemplary football scenario, we used two ARRIFLEX D-20 "film-style" digital cameras to capture both sides of the playing field as well as large parts of the stands. From the recorded left and right view images, we created a joint panoramic view with a resolution of 501 6x1400 pel (5k) using sophisticated image processing algorithms. These highly immersive football panoramas were screened with our modular, high-resolution multiprojection system during the FIFA World Cup 2006 in a 600 seat CinemaxX movie theater in Berlin providing the viewers with the feeling of actually watching the game from a good seat on the stands.