Evaluation of an Eye Tracking Technology for 3D Display Applications

Due to the bandwidth constraints of multi-view autostereoscopic display that severely restrict number of views simultaneously displayed without degrading resolution or increasing display cost unacceptably. The alternative way is the eye tracking technology, which can fluently rendering and accurately projecting the stereo video to the viewer. In order to render stereo content with respect to user's view points and to optically project the content onto the left and right eyes of the user accurately, the real-time viewer tracking technique that allows the user to move around freely when watching the autostereoscopic display is developed in this study. It comprises the face detection by using multiple eigenspaces of various lighting conditions, fast block matching for tracking four motion parameters of the user's face region. The Edge Orientation Histogram (EOH) on Real AdaBoost to improve the performance of original AdaBoost algorithm using Haar feature in OpenCV library developed by Intel is also applied in this study. Since performance of the viewer tracking autostereoscopic display is still influenced under variant environmental conditions, the robustness and efficiency of the viewer-tracking system are evaluated in this study.