Abstract
AbstractIn this thesis, we present a novel view synthesis approach which encapsulates view morphing and trifocal transfer. We can achieve the effect of having many virtual cameras, but in practice we only have two real ones. First, we use Harris corner detector to detect feature points. Then apply the normalized cross correlation and random sample consensus (RANSAC) to extract correspondences and make use of normalized direct linear transformation to solve the parameters of the multiple-view geometry.For simplifying the problem of finding dense correspondences, we assume that the scene is piecewise planar. Thus, we can make use of the homography matrices to determine the dense correspondences between the two images. The method we use does not need the strong calibration and the complex model.