Gaze direction detection from thermal camera image

This paper presents a new system to estimate the head pose of human in interactive indoor environment that has dynamic illumination change and large working space. The main idea of this system is to suggest a new morphological feature for estimating head angle from Thermal Camera. When a thermal camera shows distribution of face heat, there are obviously some morphological distributions. Applying a threshold to the heat distribution, we also obtain the different morphology image from different head yaw pose. Therefore, we can obtain the morphological shape of heat distribution of face. Through the analysis of this morphological property, the head pose can be estimated. It is simple and significantly invariant from illumination in comparison with other algorithm which adopts normal camera as a sensor. Our system can automatically segment and estimate head pose in a wide range of head motion without manual initialization like other optical flow system. As the result of experiments, we obtained the reliable head orientation data under the real-time performance.

[1]  Trevor Darrell,et al.  3D pose tracking with linear depth and brightness constraints , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[2]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[3]  Mario Romero,et al.  Tracking Head Yaw by Interpolation of Template Responses , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[4]  Hongbin Zha,et al.  Affine correspondence based head pose estimation for a sequence of images by using a 3D model , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[5]  Alexander H. Waibel,et al.  Real-Time Face and Facial Feature Tracking and Applications , 1998, AVSP.

[6]  Ruigang Yang,et al.  Model-based head pose tracking with stereovision , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[7]  Illah R. Nourbakhsh,et al.  A survey of socially interactive robots , 2003, Robotics Auton. Syst..

[8]  Emanuele Trucco,et al.  Introductory techniques for 3-D computer vision , 1998 .