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Dense Visual SLAM

The dvo_slam packages provide an implementation of our dense visual SLAM system for RGB-D cameras. The SLAM system builds upon our Dense Visual Odometry (see below). It extends the odometry approach to include a geometric error term and perform frame-to-keyframe matching. Each new keyframe is inserted into a pose graph. Additionally we search for loop closures to older keyframes. These loop closures provide additional constraints for the pose graph. The graph is incrementally optimized using the g2o framework. The output of the SLAM system are metrically consistent poses for all frame.

For source code and basic documentation visit the Github repository.

Dense Visual Odometry

The dvo packages provide an implementation of visual odometry estimation from RGB-D images for ROS. In contrast to feature-based algorithms, the approach uses all pixels of two consecutive RGB-D images to estimate the camera motion. The implementation runs in realtime on a recent CPU.

For source code and basic documentation visit the Github repository.

For questions please contact Christian Kerl.

Related Publications


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Conference and Workshop Papers
2015
[]Dense Continuous-Time Tracking and Mapping with Rolling Shutter RGB-D Cameras (C. Kerl, J. Stueckler and D. Cremers), In IEEE International Conference on Computer Vision (ICCV), 2015. ([video][supplementary][datasets]) [bibtex] [pdf]
2013
[]Dense Visual SLAM for RGB-D Cameras (C. Kerl, J. Sturm and D. Cremers), In Proc. of the Int. Conf. on Intelligent Robot Systems (IROS), 2013.  [bibtex] [pdf]
[]Robust Odometry Estimation for RGB-D Cameras (C. Kerl, J. Sturm and D. Cremers), In International Conference on Robotics and Automation (ICRA), 2013.  [bibtex] [pdf]Best Vision Paper Award - Finalist
2011
[]Real-Time Visual Odometry from Dense RGB-D Images (F. Steinbruecker, J. Sturm and D. Cremers), In Workshop on Live Dense Reconstruction with Moving Cameras at the Intl. Conf. on Computer Vision (ICCV), 2011.  [bibtex] [pdf]
Other Publications
2012
[]Odometry from RGB-D Cameras for Autonomous Quadrocopters (C. Kerl), Master's thesis, Technical University Munich, 2012.  [bibtex] [pdf]
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15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022.

15.10.2022

WACV 2023

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MCML Kick-Off

On July 27th, we are organizing the Kick-Off of the Munich Center for Machine Learning in the Bavarian Academy of Sciences.

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AI Symposium

On July 22nd 2022, we are organizing a Symposium on AI within the Technology Forum of the Bavarian Academy of Sciences.

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