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