Title :
Gaze estimation using Kinect/PTZ camera
Author :
Jafari, Roozbeh ; Ziou, Djemel
Author_Institution :
Dept. d´Inf., Univ. de Sherbrooke, Sherbrooke, QC, Canada
Abstract :
This paper describes a novel method for eye-gaze estimation under normal head movement. In this method, head position and orientation are acquired by Kinect while eye direction is obtained by PTZ camera. We propose the Bayesian multinomial logistic regression based on a variational approximation to construct a gaze mapping function from head and eyes features. Our proposed method eliminates stationary head position, awkward personal calibration procedure and active light source as three common drawbacks in most conventional techniques. The efficiency of the proposed method is validated by performance evaluation for different users under varying head position and orientation.
Keywords :
Bayes methods; approximation theory; cameras; eye; iris recognition; regression analysis; variational techniques; Bayesian multinomial logistic regression; Kinect camera; PTZ camera; eye-gaze estimation; eyes features; gaze mapping function; head features; head movement; head orientation; head position; normal head movement; pan-tilt-zoom camera; performance evaluation; variational approximation; Bayesian methods; Cameras; Estimation; Head; Iris; Logistics; Vectors;
Conference_Titel :
Robotic and Sensors Environments (ROSE), 2012 IEEE International Symposium on
Conference_Location :
Magdeburg
Print_ISBN :
978-1-4673-2705-3
DOI :
10.1109/ROSE.2012.6402633