Controlled 3D Data Fusion using Error-bounds

This paper addresses the steps associated to reconstruct a model based on a number of scans acquired with different sensor techniques. It discusses the concept of managing and operating on scans with different origins, which may have different spatial resolution, accuracy and coverage. In order to cope with these varying sensor characteristics, the article introduces the concept of error-bound which describes a point-wise uncertainty inherited from the acquisition system. Further processing steps in a 3D Model Reconstruction task need to consider this measure in order to manage varying point accuracies and correctly manage the final fusion step making a single model based on the best available information from all part information. Furthermore, the paper discusses concepts to use normal weights and normal cut-offs in the ICP algorithm and in this area we show experimental results comparing these techniques. The registration and fusion technique proposed in the article is applied on a 16 scan project aimed at accurately reconstructing an office building and some utility constructions.