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Using an Unmanned Aerial Vehicle (UAV) for documentation and inspection of civil infrastructures has become increasingly popular. One area of interest is in bridge inspection as it holds the potential of being safer, more economical, and less disruptive, with respect to traffic flow. With 3D reconstruction method, structural deficiencies and 3D models can be obtained from a 3D point cloud generated from UAV imagery data. However, shadows and water reflectivity may affect the quality of the point cloud generated from images, which causes difficulty in data processing. This paper presents a detailed workflow of removing outlier data points through the statistical filter and geometric-based filter. The experimental results showed that the statistical filter gives the best performance.