• 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