A Robust Pipeline for Facade Geometry Estimation Using AprilTags and Digital Imaging

The accurate modeling of building facades plays a critical role in architecture, urban planning, and energy efficiency. Traditional methods of facade mapping are often labor-intensive, costly, and prone to error. Recent advancements in computer vision and sensor technology have introduced innovative approaches for capturing precise geometric data, including the use of AprilTags-fiducial markers that enable efficient facade reconstruction through digital imaging techniques. This paper explores a method that involves arranging AprilTags in a grid pattern on building surfaces, capturing multiple images of the tagged facade, and using triangulation techniques to infer the 3D geometry of the structure with high accuracy. The resulting digital models have a wide range of applications, including optimizing solar panel placement, creating detailed replicas for heritage conservation, and enhancing urban planning through improved simulations of light, shadows, and heat.