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UIST2.0 Archive - 20 years of UIST
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detection

chorus detection

In Proceedings of UIST 2003
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SmartMusicKIOSK: music listening station with chorus-search function (p. 31-40)

face detection

In Proceedings of UIST 2003
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Automatic thumbnail cropping and its effectiveness (p. 95-104)

infrared detection

In Proceedings of UIST 1997
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A finger-mounted, direct pointing device for mobile computing (p. 41-42)

material detection

In Proceedings of UIST 2008
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Lightweight material detection for placement-aware mobile computing (p. 279-282)

Abstract plus

Numerous methods have been proposed that allow mobile devices to determine where they are located (e.g., home or office) and in some cases, predict what activity the user is currently engaged in (e.g., walking, sitting, or driving). While useful, this sensing currently only tells part of a much richer story. To allow devices to act most appropriately to the situation they are in, it would also be very helpful to know about their placement - for example whether they are sitting on a desk, hidden in a drawer, placed in a pocket, or held in one's hand - as different device behaviors may be called for in each of these situations. In this paper, we describe a simple, small, and inexpensive multispectral optical sensor for identifying materials in proximity to a device. This information can be used in concert with e.g., location information, to estimate, for example, that the device is "sitting on the desk at home", or "in the pocket at work". This paper discusses several potential uses of this technology, as well as results from a two-part study, which indicates that this technique can detect placement at 94.4% accuracy with real-world placement sets.

page detection

In Proceedings of UIST 2000
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Page detection using embedded tags (p. 159-160)

placement detection

In Proceedings of UIST 2008
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Lightweight material detection for placement-aware mobile computing (p. 279-282)

Abstract plus

Numerous methods have been proposed that allow mobile devices to determine where they are located (e.g., home or office) and in some cases, predict what activity the user is currently engaged in (e.g., walking, sitting, or driving). While useful, this sensing currently only tells part of a much richer story. To allow devices to act most appropriately to the situation they are in, it would also be very helpful to know about their placement - for example whether they are sitting on a desk, hidden in a drawer, placed in a pocket, or held in one's hand - as different device behaviors may be called for in each of these situations. In this paper, we describe a simple, small, and inexpensive multispectral optical sensor for identifying materials in proximity to a device. This information can be used in concert with e.g., location information, to estimate, for example, that the device is "sitting on the desk at home", or "in the pocket at work". This paper discusses several potential uses of this technology, as well as results from a two-part study, which indicates that this technique can detect placement at 94.4% accuracy with real-world placement sets.

speech detection

In Proceedings of UIST 1993
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SpeechSkimmer: interactively skimming recorded speech (p. 187-196)