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Coliseum is a multiuser immersive remote teleconferencing system designed to provide collaborative workers the experience of face-to-face meetings from their desktops. Five cameras are attached to each PC display and directed at the participant. From these video streams, view synthesis methods produce arbitrary-perspective renderings of the participant and transmit them to others at interactive rates, currently about 15 frames per second. Combining these renderings in a shared synthetic environment gives the appearance of having all participants interacting in a common space. In this way, Coliseum enables users to share a virtual world, with acquired-image renderings of their appearance replacing the synthetic representations provided by more conventional avatar-populated virtual worlds. The system supports virtual mobility-participants may move around the shared space-and reciprocal gaze, and has been demonstrated in collaborative sessions of up to ten Coliseum workstations, and sessions spanning two continents.Coliseum is a complex software system which pushes commodity computing resources to the limit. We set out to measure the different aspects of resource, network, CPU, memory, and disk usage to uncover the bottlenecks and guide enhancement and control of system performance. Latency is a key component of Quality of Experience for video conferencing. We present how each aspect of the system-cameras, image processing, networking, and display-contributes to total latency. Performance measurement is as complex as the system to which it is applied. We describe several techniques to estimate performance through direct light-weight instrumentation as well as use of realistic end-to-end measures that mimic actual user experience. We describe the various techniques and how they can be used to improve system performance for Coliseum and other network applications. This article summarizes the Coliseum technology and reports on issues related to its performance-its measurement, enhancement, and control.

Gamut mapping deals with the need to adjust a color image to fit into the constrained color gamut of a given rendering medium. A typical use for this tool is the reproduction of a color image prior to its printing, such that it exploits best the given printer/medium color gamut, namely the colors the printer can produce on the given medium. Most of the classical gamut mapping methods involve a pixel-by-pixel mapping and ignore the spatial color configuration. Recently proposed spatial-dependent approaches for gamut mapping are either based on heuristic assumptions or involve a high computational cost. In this paper, we present a new variational approach for space-dependent gamut mapping. Our treatment starts with the presentation of a new measure for the problem, closely related to a recent measure proposed for Retinex. We also link our method to recent measures that attempt to couple spectral and spatial perceptual measures. It is shown that the gamut mapping problem leads to a quadratic programming formulation, guaranteed to have a unique solution if the gamut of the target device is convex. An efficient numerical solution is proposed with promising results.