• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.37 no.5
• /
• pp.470-475
• /
• 2009

This paper is the study which is head tracker using pattern matching. Proposal algorithm obtains initial attitude of head tracker using pattern matching. Optical head tracker consists of infrared LEDs(features) which are attached helmet as pattern, stereo infrared cameras. Proposal algorithm analyzes patterns by error rate of feature distance and estimates feature characteristic number. Initial attitude of head tracker is obtained to compare map data and feature characteristic number.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.7
• /
• pp.680-687
• /
• 2008

This paper presents map creation algorithm and initial attitude estimation method for the proposed optical head tracker system. The optical head tracker system consists of the IR stereo cameras and infrared LEDs as features on the helmet. In order for the stereo camera to track the luminous LEDs, it must take in to account the light radiation from the LEDs to determine the position of the center points. The proposed map creation algorithm makes map data about the position of features center points on the helmet frame. Also, initial attitude estimation method is proposed to estimate the initial attitude and position of a pilot head from the camera frame by the use of the feature pattern on the helmet. Therefore, the head motion can be expressed with respect to the body frame of a flight.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.34 no.5
• /
• pp.81-87
• /
• 2006

In this paper, an experimental optical head tracker system is designed and constructed. The system is composed of the infrared LEDs and two infrared CCD cameras to filter out the interference of another light in the limited environment like the cockpit. Then the optical head tracker algorithm is designed by using the feature detection algorithm and the 3D motion estimation algorithm. The feature detection algorithm, used to obtain the 2D position coordinates of the features on the image plane, is implemented by using the thresholding and the masking techniques. The 3D motion estimation algorithm which estimates the motion of a pilot's head is implemented by using the extended Kalman filter (EKF). Also, we used the precise rate table to verify the performance of the experimental optical head tracker system and compared the rotational performance of this system with the inertial sensor.