Spatial uncertainty model of a three-view RGB-D camera system

Chen Zhu, Simon Bilgeri, Christoph Günther

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Multi-view stereo cameras and RGB-D cameras are widely used in robotic vision for 3D map reconstruction in navigation tasks. RGB-D cameras provide accurate depth measurements even in textureless areas, but are sensitive to distortion of its actively projected patterns. Stereo cameras are reliable if and only if there are sufficient features in the visible region. The two kinds of sensors are complementary in performance, so we combine them to a three-view RGB-D system and propose a fusion method for reliable 3D point cloud reconstruction. Furthermore, the reliability of the reconstructed map is vital for robotic navigation, so we build a spatial uncertainty model for the system, which can be easily specialized to either subsystems. The fusion method is shown to have gain in performance from the spatial uncertainty perspectives.

Original languageEnglish
Title of host publicationAdvances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings
EditorsGeorge Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ryan McMahan, Jason Jerald, Hui Zhang, Steven M. Drucker, Kambhamettu Chandra, El Choubassi Maha, Zhigang Deng, Mark Carlson
PublisherSpringer Verlag
Pages117-128
Number of pages12
ISBN (Electronic)9783319143637
DOIs
StatePublished - 2014
Event10th International Symposium on Visual Computing, ISVC 2014 - Las Vegas, United States
Duration: 8 Dec 201410 Dec 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8888
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Symposium on Visual Computing, ISVC 2014
Country/TerritoryUnited States
CityLas Vegas
Period8/12/1410/12/14

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