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In this paper we present a framework for the rendering of scenes for 3DTV applications. The goal of our work is to investigate ways to generate virtual views of a scene captured using a relatively small number of real cameras. The approach adopted uses per-pixel operations and therefore is suitable for fast parallel implementation. A depth map is implicitly generated for every of the virtual viewpoints...
We identify scene categorization as the first step towards efficient and robust depth estimation from single images. Categorizing the scene into one of the geometric classes greatly reduces the possibilities in subsequent phases. To that end, we introduce 15 typical 3D scene geometries, called stages, each having a unique depth profile and roughly corresponding to a large majority of all images. In...
Recently, methods for estimating 3D scene geometry or absolute scene depth information from 2D image content have been proposed. However, general applicability of these methods in depth estimation may not be realizable, as inconsistencies may be introduced due to a large variety of possible pictorial content. We identify scene categorization as the first step towards efficient and robust depth estimation...
Philips is realizing an end-to-end 3D display solution from 3D content creation to visualization. This development fits in our long-standing tradition of combining expertise in video processing with our strength in display development to create the most exciting and best viewing experience. Philips developed several high-quality 3D displays, ranging in resolution, viewing angle, depth experience,...
This paper describes a non-intrusive method to estimate the gaze direction of a person by using stereo cameras. First, facial features are tracked with an adapted particle filtering algorithm using factorized likelihoods to estimate the 3D head pose. Next the 3D gaze vector is calculated by estimating the eyeball center and the cornea center of both eyes. For the intended application of visual perception...
A biomechanical model of the lower urinary tract which is able to respond to input signals from a neural network is presented. The neural input is the starting point in the description of the relationships between the various physical parameters in the mechanical model of the bladder and the urethra. The cybernetics of the lower urinary tract are described on the basis of the muscle dynamics of single...
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