Randomized view planning and occlusion removal for mosaicing building facades

We present two key parts of an ongoing robotic, vision-based architectural modeling project. The first component is a randomized approach to view planning for a single ground robot scanning a building perimeter to recover a series of texture map mosaics. This algorithm generates paths that simultaneously address coverage and quality (i.e., real-valued distance and foreshortening factors). The second part is a technique for "cleaning" the captured texture maps in the presence of occlusions caused by trees, signs, people, and other foreground objects. When such occlusions comprise a minority of views a background feature can be recovered via temporal median filtering, but when they are in the majority, appearance information from other visible portions of the facade provides a critical cue to correctly complete the mosaic. We describe a novel spatiotemporal timeline-based inpainting algorithm that identifies and corrects such areas.