Meeting environments, such as conference rooms, executive briefing centers, and exhibition spaces, are now commonly equipped with multiple displays, and will become increasingly display-rich in the future. Existing authoring/presentation tools such as PowerPoint, however, provide little support for effective utilization of multiple displays. Even using advanced multi-display enabled multimedia presentation tools, the task of assigning material to displays is tedious and distracts presenters from focusing on content.
This paper describes a framework for automatically assigning presentation material to displays, based on a model of the quality of views of audience members. The framework is based on a model of visual fidelity which takes into account presentation content, audience members' locations, the limited resolution of human eyes, and display location, orientation, size, resolution, and frame rate. The model can be used to determine presentation material placement
based on average or worst case audience member view quality, and to warn about material that would be illegible.
By integrating this framework with a previous system for multi-display presentation [PreAuthor, others], we created a tool that accepts PowerPoint and/or other media input files, and automatically generates a layout of material onto displays for each state of the presentation. The tool also provides an interface allowing the presenter to modify the automatically generated layout before or during the actual presentation. This paper discusses the framework, possible application scenarios, examples of the system behavior, and our experience with system use.
We present a framework, motivated by rate-distortion theory and the human visual system, for optimally representing the real world given limited video resolution. To provide users with high fidelity views, we built a hybrid video camera system that combines a fixed wide-field panoramic camera with a controllable pan/tilt/zoom (PTZ) camera. In our framework, a video frame is viewed as a limited-frequency representation of some "true" image function. Our system combines outputs from both cameras to construct the highest fidelity views possible, and controls the PTZ camera to maximize information gain available from higher spatial frequencies. In operation, each remote viewer is presented with a small panoramic view of the entire scene, and a larger close-up view of a selected region. Users may select a region by marking the panoramic view. The system operates the PTZ camera to best satisfy requests from multiple users. When no regions are selected, the system automatically operates the PTZ camera to minimize predicted video distortion. High-resolution images are cached and sent if a previously recorded region has not changed and the PTZ camera is pointed elsewhere. We present experiments demonstrating that the panoramic image can effectively predict where to gain the most information, and also that the system provides better images to multiple users than conventional camera systems.
This paper reports our design, and implementation of an automatic lecture-room camera-management system. The motivation for building this system is to facilitate online lecture access and reduce the expense of producing high quality lecture videos. The goal of this project is a camera-management system that can perform as a human video-production team. To achieve this goal, our system collects audio/video signals available in the lecture room and uses the multimodal information to direct our video cameras to interesting events. Compared to previous work--which has tended to be technology centric--we started with interviews with professional video producers and used their knowledge and expertise to create video production rules. We then targeted technology components that allowed us to implement a substantial portion of these rules, including the design of a virtual video director, a speaker cinematographer, and an audience cinematographer. The complete system is installed in parallel with a human-operated video production system in a middle-sized corporate lecture room, and used for broadcasting lectures through the web. The system¡*s performance was compared to that of a human operator via a user study. Results suggest that our system's quality is close to that of a human-controlled system.