A novel concept of stereoscopic imaging providing a depth-of-field blur effect close to that experienced in natural vision is presented. With this concept, only a mini-volume of the reproduced three-dimensional space is displayed in full spatial resolution. This volume is centered around the current point of fixation of the viewer. In an exploratory study the concept of a so-called "depth of-interest" (DOI) display was evaluated. Subjects assessed computer-generated 3D images with different depth-selective filtering characteristics (i.e., varying in-depth extents of the mini-volume with full resolution). Results indicate that the DOI display can indeed improve 3D viewing comfort. Apparently, a somewhat smaller depth of field than experienced in natural vision is preferred in stereoscopic image representations
The mismatch between dynamic ranges of intensities in nonuniformly illuminated portrait scenes and of intensities reproducible on common display devices is addressed. In particular, such mismatches appear quite often in videophone and videoconferencing situations. Displayed portrait images with no details visible in some facial regions result from them, and lead in turn to a reduced impression of telepresence. A novel image processing approach for dynamic range compression of portrait images is presented in this paper. Unlike conventional methods, it provides compressed images with a most natural appearance. The basic idea is to simulate a more uniform scene illumination in the video signals of portrait images. This requires knowledge about the scene's reflectance function. Based on scale-space filtering, an edge discrimination technique is developed that distinguishes intensity edges caused by reflectance from edges caused by illumination at smoothly curved surfaces. This facilitates an estimation of the reflectance component from the intensity distribution of portrait images using an extension of the classical lightness computation approach
Lightness algorithms, which have been proposed as a model for human vision, are aimed at recovering surface reflectance in a close approximation. They attempt to separate reflectance data from illumination data by thresholding a spatial derivative of the image intensity. This, however, works only reliable in a world of plane Mondrians. An extension of the classical lightness approach of Land and McCann (1971) to curved surfaces is presented. Assuming smooth surfaces with Lambertian reflection properties and leaving aside occlusions and cast shadows, the separation of those components of the intensity gradient due to reflectance from those due to irradiance is posed as a constraint minimization problem. To do so, two classification operators were introduced which identify potential reflectance and irradiance data using a scale-space filtering approach. Two exemplary applications of the proposed extended lightness algorithm in the field of visual telecommunications are presented: (i) the simulation of more uniformly illuminated videophone portrait scenes to give dynamic range compressed images with a most realistic appearance and (ii) the synthesis of videophone portrait images from model-based coded data with a correct illumination effect. In both applications, the extended lightness algorithm is employed for estimating the reflectance functions at facial surfaces. Results obtained by applying the extended lightness algorithm are compared with results obtained by conventional methods known from literature.
Head movement data were collected from 128 subjects during an experimental study using four ditYerent videoconferencing set-ups (factorial design of monoscopic / stereoscopic set-ups with / without motion parallax). The data include various parameters and are relevant inter alia for terminal and display designers.
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