The new method is up to 7 times faster than the best state-of-the-art approach. A help for professionals and researchers in the domain of architecture, civil engineering and visual computing.
As a concrete example, it’s now possible to estimate reliable normal vectors in less than 10 seconds for an input model composed by 700'000 points. More than 65 seconds faster than using a reference state-of-the-art method. The technique can be easily included in 3D point-cloud processing software. Thus, a new useful tool available to process data scanned with LIDAR or TOF-camera.
Claudio Mura, Gregory Wyss and Renato Pajarola have won the 2nd Best Paper Award at the CGI 2018 conference – in recognition for their work, described in the paper «Robust Normal Estimation in Unstructured 3D Point Clouds by Selective Normal Space Exploration».