KEYWORDS: 3D image processing, Video, 3D displays, Image segmentation, Image processing, Atomic force microscopy, Visualization, Cameras, Motion estimation, Video processing
Philips provides autostereoscopic three-dimensional display systems that will bring the next leap in visual experience,
adding true depth to video systems. We identified three challenges specifically for 3D image processing: 1) bandwidth
and complexity of 3D images, 2) conversion of 2D to 3D content, and 3) object-based image/depth processing. We
discuss these challenges and our solutions via several examples. In conclusion, the solutions have enabled the market
introduction of several professional 3D products, and progress is made rapidly towards consumer 3DTV.
We propose the 'Dynamic Dimension' system that enables simultaneous viewing of 3D and monoscopic content on glasses-based stereo displays (e.g. CRT, Plasma, LCD). A viewer can choose to wear glasses and see content in 3D, or he may decide not to wear glasses, and see high-quality monoscopic content. The Dynamic Dimension system is based on simple image processing such as addition and subtraction. The input images can be captured by a triple camera setup or be rendered from so-called RGBD video, an ad-hoc standard for 3D video. From several subjective tests, we conclude that Dynamic Dimension produces a very much present and appealing 3D effect, while the monoscopic image quality remains high and totally unaffected.
KEYWORDS: Cameras, 3D modeling, Field programmable gate arrays, Computer programming, Signal processing, Motion models, Digital signal processing, Clocks, Panoramic photography, Telecommunications
In this paper we address the real time synthesis of virtual vies for multi viewpoint stereoscopic systems. For the viewpoint dependent generation of virtual vies two approaches can be adopted; a dynamic 3D-model reconstruction of the recorded scene from which the desired virtual views are derived or a disparity compensated interpolation strategy. The latter approach is most feasible for real time system. After a brief review of possible hardware choices we describe, as an example of the disparity compensated strategy, a dynamic programming based disparity estimation algorithm and a disparity compensated interpolation algorithm. For efficient implementation an alternative disparity representation format is presented. Both algorithms are specifically designed for hardware implementation to meet real time constraints. Hardware architectures and implementation considerations are given. Simulations show high quality results for typical teleconferencing scenes. A similar version of the interpolation algorithm is realized and successfully demonstrated in the PANORAMA project.
Stereo matching is fundamental to applications such as 3D visual communications and depth measurements. There are several different approaches towards this objective, including feature-based methods, block-based methods, and pixel-based methods. Most approaches use regularization to obtain reliable fields. Generally speaking, when smoothing is applied to the estimated depth field, it results in a bias towards surfaces that are parallel to the image plane. This is called fronto-parallel bias. Recent pixel-based approaches claim that no disparity smoothing is necessary. In their approach, occlusions and objects are explicitly modeled. But these models interfere each others in the case of slanted objects and result in a fragmented disparity field. In this paper we propose a disparity estimation algorithm with explicit modeling of object orientation and occlusion. The algorithm incorporates adjustable resolution and accuracy. Smoothing can be applied without introducing the fronto-parallel bias. The experiments show that the algorithm is very promising.
In this paper we present a combination of there steps to code a disparity map for 3D teleconferencing applications. First we introduce a new disparity map format, the chain map, which has a very low inherent redundancy. Additional advantages of this map are: one single bidirectional map instead of the usual two unidirectional vector fields, explicit indication of occlusions, no upper or lower bound on disparity values, no disparity offset, easy generation by disparity estimators and easy interpretation by image interpolators. In a second step, we apply data reduction on the chain map. The reduction is a factor too, thereby losing explicit information about the position of occlusion areas. An algorithm for image interpolation in absence of occlusion information is presented. The third step involves entropy coding, both lossless and lossy. A scheme specially suited for the chain map has been developed. Although the codec is based on a simple prediction process without motion compensation, compression ratios of 20 to 80 can be achieved with typical teleconferencing images. These results are comparable to those obtained by complex schemes based on 2D/3D motion compensation using disparity vector fields.
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