Refining building facade models with images

Laser data and optical data have a complementary nature to 3D features’ extraction. Building reconstruction by fusion of the two data sources can reduce the complexity of approaches from either side. In this paper we present a model refinement method, which uses the strong lines extracted from close-range images to improve building models reconstructed from terrestrial laser point clouds. First, model edges are projected from model space to image space. Then significant line features are extracted from an image with Canny edge detector and Hough transformation. Each model edge is then compared with its neighboring image lines to determine the best match. Finally the model edges are updated according to their corresponding image lines. The refinement process not only fixes certain geometry errors of the original models, but also adapts the models to the image data, so that more accurate texturing is achieved.