Abstract
In this thesis, we propose a view interpolation algorithm to synthesize novel face images at different viewpoints from a single non-frontal face image. Based on the symmetry assumption of human faces, we mirror the original non-frontal face image to obtain another basis image. A 3D generic head model is used to estimate the face pose by manually labeling a small set of feature points as input to the system. The dense matching between two basis images is computed from 2D-3D RBF mapping, 3D-2D perspective projection and optical flow computation. To solve the self-occlusion problem in point correspondence, a bi-directional morphing algorithm is used to obtain the forward and the backward interpolated images. Finally, the final view-interpolated image is obtained by combining the above two interpolated images with an appropriate weighting function. Experimental results show satisfactory view interpolation results from a single face image.