3D Facade Reconstruction Using the Fusion of Images and LiDAR: A Review

Abstract

Three-dimensional (3D) urban reconstruction becomes increasingly crucial in many application areas, such as entertainment, urban planning, digital mapping. To achieve photorealistic 3D urban reconstruction, the detailed reconstruction of building facades is the key. Light Detection and Ranging (LiDAR) point clouds and images are the two most important data types for 3D urban reconstruction, which are complementary regarding data characteristic. LiDAR scans are sparse and noisy but contain the precise depth data, whereas images can offer the color and high-resolution data but no depth information. In recent years, an increasing number of studies show that the fusion of LiDAR point clouds and images can attain better 3D reconstruction results than a single data type. In this paper, we aim to provide a systematic review of the research in the area of the 3D facade reconstruction based on the fusion of LiDAR and images. The reviewed studies are classified by the different usage of images in the reconstruction process. We hope that this research could help future researchers have a more clear understanding of how existing studies leverage the data in LiDAR scans and images and promote more innovations in this area.