Title of article :
A neural network based real-time gaze tracker
Author/Authors :
Piratla، Nischal M. نويسنده , , Jayasumana، Anura P. نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2002
Pages :
-178
From page :
179
To page :
0
Abstract :
A real-time gaze-tracking system that estimates the userʹs eye gaze and computes the window of focused view on a computer monitor has been developed. This artificial neural network based system can be trained and customized for an individual. Unlike existing systems in which skin color features and/or other mountable equipment are needed, this system is based on a simple nonintrusive camera mounted on the monitor. Gaze point is accurately estimated within a 1 in. on a 19in. monitor with a CCD camera having a 640×480 image resolution. The system performance is independent of userʹs forward and backward as well as upward and downward movements. The gaze-tracking system implementation and the factors affecting its performance are discussed and analyzed in detail. The features and implementation methods that make this system real-time are also explained.
Keywords :
demersal fish , feeding , foraging behaviour , prey selection , polychaetes , resource partitioning
Journal title :
Journal of Network and Computer Applications
Serial Year :
2002
Journal title :
Journal of Network and Computer Applications
Record number :
58674
Link To Document :
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