Display control based on eye gaze estimation

Detecting and tracking eye gaze is an active research area and significant progress has been made in this area in the past decades. However, challenge remains due to the differences between individual's eyes, variability in light condition, scale and occlusion. Works on eye location and eye movements have a large number of applications and is an important part of biometrics, human-computer interaction and face detection. Based on the current works and applications on eye gaze detection, the author notice, however, applying eye gaze information on human-computer interaction still lacks of enough work on it. This paper proposes a novel pipeline of employing eye gaze information for display control based on the video captured by integrated camera. The proposed pipeline shows that, despite the low quality of the video and light condition, eye gaze can still be estimated and display of the screen can be controlled accordingly.

[1]  Pong C. Yuen,et al.  Multi-cues eye detection on gray intensity image , 2001, Pattern Recognit..

[2]  Laura Chamberlain Eye Tracking Methodology; Theory and Practice , 2007 .

[3]  John Paulin Hansen,et al.  Robustifying Eye Interaction , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[4]  Myung Jin Chung,et al.  A novel non-intrusive eye gaze estimation using cross-ratio under large head motion , 2005, Comput. Vis. Image Underst..

[5]  Takahiro Ishikawa,et al.  Passive driver gaze tracking with active appearance models , 2004 .

[6]  Rafael Cabeza,et al.  Gaze Tracking System Model Based on Physical Parameters , 2007, Int. J. Pattern Recognit. Artif. Intell..

[7]  Tommy Strandvall,et al.  Eye Tracking in Human-Computer Interaction and Usability Research , 2009, INTERACT.

[8]  Arnon Amir,et al.  Framerate pupil detector and gaze tracker , 1999, ICCV 1999.

[9]  Mads Nielsen,et al.  Eye typing using Markov and active appearance models , 2002, Sixth IEEE Workshop on Applications of Computer Vision, 2002. (WACV 2002). Proceedings..

[10]  I. King,et al.  Localized Principal Component Analysis Learning for Face Feature Extraction and Recognition , 1997 .

[11]  Peter W. Hallinan Recognizing human eyes , 1991, Optics & Photonics.

[12]  Jeffrey B. Mulligan,et al.  Implicit Calibration of a Remote Gaze Tracker , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[13]  Dan Witzner Hansen,et al.  Eye tracking in the wild , 2005, Comput. Vis. Image Underst..

[14]  Andrew Blake,et al.  Sparse and Semi-supervised Visual Mapping with the S^3GP , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[15]  Robert Mariani,et al.  Face detection and precise eyes location , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[16]  Qiang Ji,et al.  In the Eye of the Beholder: A Survey of Models for Eyes and Gaze , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Alex Pentland,et al.  View-based and modular eigenspaces for face recognition , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[18]  Slavko Milekic The More You Look the More You Get: Intention-Based Interface Using Gaze-Tracking. , 2003 .

[19]  K. Hyoki,et al.  Quantitative electro-oculography and electroencephalography as indices of alertness. , 1998, Electroencephalography and clinical neurophysiology.