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dc.contributor.authorNewman, William
dc.contributor.authorFranzel, David
dc.contributor.authorMatsumoto, Takeshi
dc.contributor.authorLeibbrandt, Richard Eduard
dc.contributor.authorLewis, Trent Wilson
dc.contributor.authorLuerssen, Martin Holger
dc.contributor.authorPowers, David Martin
dc.date.accessioned2011-12-02T01:44:33Z
dc.date.available2011-12-02T01:44:33Z
dc.date.issued2010
dc.identifier.citationNewman, 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.en
dc.identifier.issn1098-7576
dc.identifier.urihttp://hdl.handle.net/2328/25738
dc.description.abstractFast 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.en
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Computer Society (IEEE Publishing)en
dc.subjectCamerasen
dc.subjectCorrelationen
dc.subjectObject recognitionen
dc.subjectHistogramsen
dc.titleHybrid world object tracking for a virtual teaching agenten
dc.typeArticleen
dc.rights.licenseIn Copyright
local.contributor.authorOrcidLookupLeibbrandt, Richard Eduard: https://orcid.org/0000-0003-2442-0782en_US
local.contributor.authorOrcidLookupLewis, Trent Wilson: https://orcid.org/0000-0002-4025-4019en_US
local.contributor.authorOrcidLookupPowers, David Martin: https://orcid.org/0000-0001-5998-2262en_US


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