Epipolar geometry estimation and its application to image coding

This paper presents image-based rendering related techniques: (1) a computer vision technique to estimate accurate epipolar geometry and (2) an image coding technique to compress multiple-viewpoint images, which are stored for reconstruction of any arbitrary view of 3-D object, with the epipolar geometry. Unlike other epipolar geometry estimation techniques based on the correct sets of feature point correspondence, which is hardly given in practice, the proposed method minimizes absolute luminance difference between two images with respect to seven epipolar geometry parameters. In the framework of block matching, the absolute luminance difference between the two images can be represented by the seven parameters with which a nonlinear robust regression follows. We apply the epipolar geometry estimation technique to multiple-viewpoint image coding. That practically contributes to improving the coding efficiency, where more than 1000 viewpoint images are coded by a type of predictive coding based on epipolar geometry. The experimental results show that the compression ratio attains to 1/100 and more.