Schoenenberger, Yann MikaëlParatte, JohannVandergheynst, Pierre2015-06-112015-06-112015-06-11201510.1109/3DTV.2015.7169366https://infoscience.epfl.ch/handle/20.500.14299/115018Noisy 3D point clouds arise in many applications. They may be due to errors when creating a 3D model from images or simply to imprecise depth sensors. Point clouds can be given geometrical structure using graphs created from the similarity information between points. This paper introduces a method that uses this graph structure and convex optimization methods to denoise 3D point clouds. A short discussion presents how those methods naturally generalize to time-varying inputs such as 3D point cloud time series.3D point cloud denoisingconvex optimizationspatio-temporal denoisinggraph signal processingtext::conference output::conference paper not in proceedings