3-D Image Reconstruction Based On Computer Vision

The two images of the same scene with different viewpoints is studied in this massage. Based on computer vision, with wavelet transformation feature points extraction, fundamental matrix is gotten by feature points matching. The image-based 3D is reconstructed by the theory of epipolar geometry.At first the theory of computer vision is proposed. The principle of epipolar geometry is introduced. And arithmetic about how to solve fundamental matrix is discussed. Then the theory of vision stereo matching and 3-D reconstruction are introduced.Vision stereo matching is one of the fundamental and significant problems in the study of the computer vision and contactless measurements. This technique makes it possible to reproduce a three-dimensional stereo by getting fundamental matrix through matching pixels. But matching is the most difficult problem to be solved completely. In this article, image is matched by feature points. The characteristic of corner points and feature points extracted by wavelet transformation are presented and compared. In this passage a nicer feature points matching method is proposed. At first, initial feature points pairs are being found with parallax method and area supporting. In this way more correct feature point pairs are founded out and initial feature point pairs aggregation is built up. Then the aggregation is optimized continually through fundamental matrix method. On one hand, error point pairs are moved out. On the other hand, accurate fundamental matrix is built.At last,the hierarchical structure of 3-D reconstruction technology is introduced. Experiments on the real images show that the algorithm in this work is applicable and effective. And a proportion of matching point pairs is reconstructed in projective space.