3D Reconstruction Approach for Outdoor Scene Based on Multiple Point Cloud Fusion

Multiple point cloud fusion is one of the most widely used methods for outdoor scene 3D reconstruction. However, being based on the traditional registration methods, their performance critically influences the quality of the 3D reconstruction. This paper proposes a 3D reconstruction method that fuses different sensors point cloud, which comes from laser scanning and structure from motion. First, a scale-based principal component analysis-iterative closest point (a scaled PCA-ICP) algorithm is addressed to eliminate different scales of two view points. Further, the feature points are extracted automatically for accurate registration by analyzing the persistence of feature points with discretely sampling on different sphere radii. Finally, the optimization ICP method is used to match multiple point cloud to achieve accurate reconstruction of outdoor scenes robustly. The experimental evaluation demonstrates that the proposed method is able to produce reliable registration results for the outdoor scene.