Source:http://linkedlifedata.com/resource/pubmed/id/15827002
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Predicate | Object |
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rdf:type | |
lifeskim:mentions | |
pubmed:dateCreated |
2005-4-13
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pubmed:abstractText |
A concern with video eye movement tracking is that movement of the camera headset relative to the head creates an artifact of eye movement in pupil-detection software. We describe the development of, and compare the results of, three automatic image processing algorithms to measure camera movement. The best of the algorithms has an average accuracy of 1.3 pixels, equivalent to 0.49 deg with our eye tracking system.
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pubmed:grant | |
pubmed:language |
eng
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pubmed:journal | |
pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:month |
Apr
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pubmed:issn |
0077-8923
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pubmed:author | |
pubmed:issnType |
Print
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pubmed:volume |
1039
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
470-6
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pubmed:dateRevised |
2007-11-14
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pubmed:meshHeading |
pubmed-meshheading:15827002-Automation,
pubmed-meshheading:15827002-Eye Movements,
pubmed-meshheading:15827002-Eyelids,
pubmed-meshheading:15827002-Humans,
pubmed-meshheading:15827002-Models, Biological,
pubmed-meshheading:15827002-Motor Activity,
pubmed-meshheading:15827002-Photography,
pubmed-meshheading:15827002-Posture,
pubmed-meshheading:15827002-Video Recording
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pubmed:year |
2005
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pubmed:articleTitle |
Automatic detection of camera translation in eye video recordings using multiple methods.
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pubmed:affiliation |
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21287, USA. Faisal@jhu.edu
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pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, Non-P.H.S.,
Research Support, Non-U.S. Gov't,
Research Support, N.I.H., Extramural
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