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Collaboration often relies on all group members having a shared view of a single-user application. A common situation is a single active presenter sharing a live view of her workstation screen with a passive audience, using simple hardware-based video signal projection onto a large screen or simple bitmap-based sharing protocols. This offers simplicity and some advantages over more sophisticated software-based replication solutions, but everyone has the exact same view of the application. This conflicts with the presenter's need to keep some information and interaction details private. It also fails to recognize the needs of the passive audience, who may struggle to follow the presentation because of verbosity, display clutter or insufficient familiarity with the application.Views that cater to the different roles of the presenter and the audience can be provided by custom solutions, but these tend to be bound to a particular application. In this paper we describe a general technique and implementation details of a prototype system that allows standardized role-specific views of existing single-user applications and permits additional customization that is application-specific with no change to the application source code. Role-based policies control manipulation and display of shared windows and image buffers produced by the application, providing semi-automated privacy protection and relaxed verbosity to meet both presenter and audience needs.

This paper presents a novel image editing program emphasizing easy selection and manipulation of material found in informal, casual documents such as sketches, handwritten notes, whiteboard images, screen snapshots, and scanned documents. The program, called ScanScribe, offers four significant advances. First, it presents a new, intuitive model for maintaining image objects and groups, along with underlying logic for updating these in the course of an editing session. Second, ScanScribe takes advantage of newly developed image processing algorithms to separate foreground markings from a white or light background, and thus can automatically render the background transparent so that image material can be rearranged without occlusion by background pixels. Third, ScanScribe introduces new interface techniques for selecting image objects with a pointing device without resorting to a palette of tool modes. Fourth, ScanScribe presents a platform for exploiting image analysis and recognition methods to make perceptually significant structure readily available to the user. As a research prototype, ScanScribe has proven useful in the work of members of our laboratory, and has been released on a limited basis for user testing and evaluation.