A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
Robust Feature-Preserving Denoising of 3D Point Clouds
2016 Fourth International Conference on 3D Vision (3DV)
The increased availability of point cloud data in recent years has lead to a concomitant requirement for high quality denoising methods. This is particularly the case with data obtained using depth cameras or from multi-view stereo reconstruction as both approaches result in noisy point clouds and include significant outliers. Most of the available denoising methods in the literature are not sufficiently robust to outliers and/or are unable to preserve finescale 3D features in the denoiseddoi:10.1109/3dv.2016.17 dblp:conf/3dim/HaqueG16 fatcat:7l6ek5ldeneojajnihath5d2pq