Consolidation of Low-quality Point Clouds from Outdoor Scenes

Release time:2016-04-25

Journal:Computer Graphics Forum

Abstract:The emergence of laser/LiDAR sensors, reliable multi-view stereo techniques and more recently consumer depth cameras have brought point clouds to the forefront as a data format useful for a number of applications. Unfortunately, the point data from those channels often incur imperfection, frequently contaminated with severe outliers and noise. This paper presents a robust consolidation algorithm for low-quality point data from outdoor scenes, which essentially consists of two steps: 1) outliers filtering and 2) noise smoothing. We first design a connectivity-based scheme to evaluate outliernes

Co-author:Jun Wang, Kai Xu, Junjie Cao, Shengjun Liu, Ligang Liu, Zeyun Yu, Xianfeng David Gu

Indexed by:Applied Research

Document Type:J

Volume:32

Issue:5

Page Number:207–216

Translation or Not:no

Date of Publication:2013-08-01

Links to published journals:http://xueshu.baidu.com/s?wd=paperuri%3A%28ddbee0b223e32a35b67ccd246a91aeb1%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1111%2Fcgf.12187%