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Gaze Behavior Detection System Based on the Object Image

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dc.contributor.advisor Hong, Sangjin en_US
dc.contributor.author Huang, Yunkai en_US
dc.contributor.other Department of Electrical Engineering. en_US
dc.date.accessioned 2017-09-20T16:52:45Z
dc.date.available 2017-09-20T16:52:45Z
dc.date.issued 2013-12-01 en_US
dc.identifier.uri http://hdl.handle.net/11401/77468 en_US
dc.description 44 pg. en_US
dc.description.abstract This thesis presents a design methodology of a low-cost noninvasive gaze tracking system to detect gaze behavior when user is browsing internet or reading material on computer. The user's face image is captured and processed in real-time. By means of C++ and OpenCV library, the system detects face, eye region with Haar feature-based cascade classifier. Eye center is detected by contouring dark area in eye region and finding the center of largest area among contoured dark areas. The detected eye center is mapped to gaze point on computer screen after four point calibration. The average angular error is 1.96 degree, which is comparable to other proposed techniques. During the experiment, the gaze point is displayed real-time with eye movement, and its coordinate as well as the gazed object are recorded in file. The system represents image information in unit area, object, scene, and frame hierarchy structure. With the gaze point data and image information, it is able to analyze gaze duration among objects and understand user's gaze behavior. en_US
dc.description.sponsorship This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. en_US
dc.format Monograph en_US
dc.format.medium Electronic Resource en_US
dc.language.iso en_US en_US
dc.publisher The Graduate School, Stony Brook University: Stony Brook, NY. en_US
dc.subject.lcsh Computer engineering en_US
dc.subject.other camera, gaze behavior detection, gaze tracking, opencv en_US
dc.title Gaze Behavior Detection System Based on the Object Image en_US
dc.type Thesis en_US
dc.mimetype Application/PDF en_US
dc.contributor.committeemember Hong, Sangjin en_US
dc.contributor.committeemember Milder, Peter. en_US

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