48.3: Viewer's Eye Position Estimation using Single Camera

Abstract

AbstractIn this paper, we propose a system that can estimate viewer's eye position using single camera in an autostereoscopic 3D display, which adopts Active Appearance Model (AAM), Elastic Bunch Graph Matching (EBGM) and Pose from Orthography and Scaling with ITerations (POSIT) algorithms for the eye position calculation. AAM is one of the most prominent facial feature detection algorithms for estimating viewer's eye position. However, this algorithm also has an issue in accuracy. EBGM is also known to be a very successful algorithm for the detection of viewer's facial feature points. Also, POSIT is known to calculate 3D pose from 2D image. In this paper, we propose a way to improve the accuracy of viewer's eye position by applying algorithms, AAM for initial estimation of facial features, EBGM for accurate facial feature position calculation and POSIT for calculation 3D facial position. The system estimates 3D facial position from extracted facial feature points to calculate accurate eye position. To calculate accurate eye position, we adopt POSIT algorithm when the viewer's face is rotated. It is verified through experiments that the newly proposed method performs better than existing method that uses single camera.