NDLI: A real-time framework for eye detection and tracking

Content Provider	Springer Nature Link
Author	Hamshari, Hussein O. Beauchemin, Steven S.
Copyright Year	2010
Abstract	Epidemiological studies indicate that automobile drivers from varying demographics are confronted by difficult driving contexts such as negotiating intersections, yielding, merging and overtaking. We aim to detect and track the face and eyes of the driver during several driving scenarios, allowing for further understanding of a driver’s visual search pattern behavior. Traditionally, detection and tracking of objects in visual media has been performed using specific techniques. These techniques vary in terms of their robustness and computational cost. This research proposes a real-time framework that is built upon a foundation synonymous to boosting, which we extend from learners to trackers and demonstrate that the idea of an integrated framework employing multiple trackers is advantageous in forming a globally strong tracking methodology. In order to model the effectiveness of trackers, a confidence parameter is introduced to help minimize the errors produced by incorrect matches and allow more effective trackers with a higher confidence value to correct the perceived position of the target.
Starting Page	235
Ending Page	245
Page Count	11
File Format	PDF
ISSN	18618200
Journal	Journal of Real-Time Image Processing
Volume Number	6
Issue Number	4
e-ISSN	18618219
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-10-10
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Facial feature Recognition Detection Tracking Real-time Signal, Image and Speech Processing Pattern Recognition Multimedia Information Systems Computer Graphics Image Processing and Computer Vision
Content Type	Text
Resource Type	Article
Subject	Information Systems

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