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Please use this identifier to cite or link to this item: http://hdl.handle.net/2328/25738

Title: Hybrid world object tracking for a virtual teaching agent
Authors: Newman, William
Franzel, David
Matsumoto, Takeshi
Leibbrandt, Richard Eduard
Lewis, Trent
Luerssen, Martin Holger
Powers, David Martin
Keywords: Cameras
Correlation
Object recognition
Histograms
Issue Date: 2010
Publisher: Institute of Electrical and Electronics Engineers Computer Society (IEEE Publishing)
Citation: Newman, W., Franzel, D. and Matsumoto, T. et al. 2010. Hybrid world object tracking for a virtual teaching agent . The 2010 International Joint Conference on Neural Networks (IJCNN), 1-9.
Abstract: Fast algorithms and heuristics for real-time object recognition and tracking have enabled a new hybrid world technology in which one can manipulate a real world object and have its virtual world counterpart move correspondingly. This technology has been developed as part of a teaching head platform that was initially designed for language teaching but is now also being used in a range of health-oriented contexts. In this paper, the requirements of the technology are motivated and elucidated, with direct comparison of our proposed heuristics with well known object recognition algorithms.
URI: http://hdl.handle.net/2328/25738
ISSN: 1098-7576
Appears in Collections:Computer Science, Engineering and Mathematics - Collected Works

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