Globally Consistent Dense Real-Time 3D Reconstruction from RGBD Data

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


In this work, we present a dense 3D reconstruction
framework for RGBD data that can handle loop closure and
pose updates online. Handling updates online is essential to get
a globally consistent 3D reconstruction in real-time. We also
introduce fused depth maps for each keyframe that contain
the fused depths of all associated frames to greatly increase
the speed for model updates. Furthermore, we show how we
can use integration and de-integration in a volumetric fusion
system to adjust our model to online updated camera poses.
We build our system on top of the InfiniTAM framework to
generate a model from the semi-dense, keyframe based ORB
SLAM2. We extensively evaluate our system on real world and
synthetic generated RGBD data regarding tracking accuracy
and surface reconstruction.
Original languageEnglish
Title of host publicationProceedings of the OAGM Workshop 2018
Subtitle of host publicationMedical Image Analysis
EditorsMartin Welk, Martin Urschler, Peter M. Roth
Place of PublicationGraz
PublisherVerlag der Technischen Universität Graz
Number of pages7
ISBN (Electronic)978-3-85125-603-1
Publication statusPublished - 2018
EventAnnual OAGM Conference: Medical Image Analysis: OAGM 2018 - Hall/Tirol, Austria
Duration: 15 May 201816 May 2018


WorkshopAnnual OAGM Conference: Medical Image Analysis


  • 3D reconstruction
  • RGBD
  • volumetric fusion
  • SLAM


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