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Authors: Boyle, Michael
Edwards, Christopher
Greenberg, Saul
Keywords: Computer Science
Issue Date: 8-Jun-2000
Abstract: Video-based media spaces are designed to support casual interaction between intimate collaborators. Yet transmitting video is fraught with privacy concerns. Some researchers suggest that the video stream be 'filtered' to mask out potentially sensitive information. While a variety of filtering techniques exist, they have not been evaluated for how well they safeguard privacy. In this paper, we analyze how a blur and a pixelize video filter might impact both awareness and privacy in a media space. Each filter is considered at nine different levels of fidelity, ranging from heavily applied filter levels that mask almost all information, to lightly applied filters that reveal almost everything. We examined how well observers of several filtered video scenes extract particular awareness cues: the number of actors; their posture (moving, standing, seated); their gender; the visible objects (basic to detailed); and how available people look (their busyness, seriousness and approachability). We also examined the privacy-preserving potential of each filter level in the context of common workplace activities. Our results suggest that the blur filter, and to a lesser extent the pixelize filter, have a level suitable for providing awareness information while safeguarding privacy.
Appears in Collections:Greenberg, Saul

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