DocumentCode :
3863393
Title :
A novel method for eye tracking and blink detection in video frames
Author :
Leo Pauly;Deepa Sankar
Author_Institution :
Division of Electronics and Communication Engineering, School of Engineering, Cochin University of Science and Technology, Kochi - 682022, Kerala, India
fYear :
2015
Firstpage :
252
Lastpage :
257
Abstract :
This paper presents a novel method for eye tracking and blink detection in the video frames obtained from low resolution consumer grade web cameras. It uses a method involving Haar based cascade classifier for eye tracking and a combination of HOG features with SVM classifier for eye blink detection. The presented method is non intrusive and hence provides a comfortable user interaction. The eye tracking method has an accuracy of 92.3% and the blink detection method has an accuracy of 92.5% when tested using standard databases and a combined accuracy of 86% when tested under real world conditions of a normal room.
Keywords :
"Feature extraction","Databases","Face","Gaze tracking","Cameras","Support vector machines","Classification algorithms"
Publisher :
ieee
Conference_Titel :
Computer Graphics, Vision and Information Security (CGVIS), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/CGVIS.2015.7449931
Filename :
7449931
Link To Document :
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