3D reconstruction based on a complex constrain matching algorithm

摘要

The precision of stereo matching directly influence the result of 3D reconstruction from images, a matching method is proposed to increase matching accuracy. Two pictures are taken for an object in different angle using a digital camera, then the feature points are extracted from the two images. After that, the initial matching is firstly done for the image feature points, then accurate matching is performed by use of affine transformation constrain, epipolar geometry constrain and gray scale relativity constrain comprehensively. Finally the accurate matching points are utilized to reconstruct the 3D points, which are filtered, smoothed, triangulated and textured to get a true 3D model Experimental results show that this algorithm converges fast and can increase matching accuracy effectively.