In this paper we address the problem of the recovery of a realistic textured model from an image sequence without any prior knowledge either about the parameters of the cameras, or about their motion. Firstly, using various computer vision tools, we establish correspondences between the image pairs and estimate the fundamental matrix. Secondly, using epipolar geometry constraints, we can obtain the rectified image pairs by a novel rectification method, where the epipolar lines coincide with the image scan-lines. Furthermore, we can make dense stereo matching for original image pairs rapidly and simply. Thirdly, in self-calibration, the prior knowledge of orthogonal wall planes and the orthogonal and parallels line is formulated as constraints on the absolute quadric. Finally, the 3D Euclidean models can be built through self-calibration and matching Delaunay triangulation. A large number of experimental results show that this method increases the speed and accuracy of the reconstructed 3D model and the obtained 3D models are more realistic. Keywords 3D reconstruction, epipolar constraint, self-calibration, rectification, dense matching.