Abstract: In 3D reconstruction from uncalibrated views, SIFT matching has a high probability of outliers and the traditional RANSAC algorithm has a bad performance for elimination of outliers. To address this issue, this paper proposes an algorithm based on improved RANSAC and slope statistics. Firstly, the proposed approach makes RANSAC be more controllable, and improves the traditional RANSAC by enhancing the epipolar constraint. Secondly, in order to reduce computation cost and speed up the convergence rate of RANSAC, we present an iterative algorithm called consistency of slope to eliminate parts of outliers before RANSAC. Considering this algorithm is ineffective for the sharply rotated or inverted image pairs, this paper puts forward a fast algorithm called slope statistics based on coordinate transformation to complete the partial elimination for such image pairs in advance. Experiments on the testing image sequence from the professional website and multiple sets of self-photograph image pairs under different scenes which have rich repetitive texture and serious occlusion of pedestrians are presented, and average symmetric epipolar distance is less than 0.7 pixels. The experimental results show that the proposed algorithm is more robust and has better real-time performance than the existing algorithms. Finally, this paper introduces a method called consistency of depth to remove the points beyond reconstruction plan automatically. We complete texture paste operations by Open GL after obtaining 3D coordinates of the feature points, and clearly show details of the scene.