Title :
Gaze tracking by Binocular Vision and LBP features
Author :
Lu, Hu-chuan ; Wang, Chao ; Chen, Yen-wei
Author_Institution :
Dept. of Electron. Eng., Dalian Univ. of Technol., Dalian, China
Abstract :
In this paper, a new method for eye gaze tracking is proposed under natural head movement. In this method, Local-Binary-Pattern Texture Feature (LBP) is adopted to calculate the eye features according to the characteristic of the eye, and a precise Binocular Vision approach is used to detect the space coordinate of the eye. The combined features of space coordinates and LBP features of the eyes are fed into Support Vector Regression (SVR) to match the gaze mapping function, in the hope of tracking gaze direction under natural head movement. The experimental results prove that the proposed method can determine the gaze direction accurately.
Keywords :
eye; image texture; object detection; regression analysis; support vector machines; visual perception; binocular vision; eye gaze tracking; gaze direction; gaze mapping function; local-binary-pattern texture feature; natural head movement; space coordinate; support vector regression; Calibration; Cameras; Chromium; Eyes; Head; Layout; Optical reflection; Polynomials; Space technology; Tracking;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761019