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Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich

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Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

More


Research Interests

Correspondence Problems, Segmentation, SLAM, Variational Methods, Partial Differential Equations

Brief Bio

Frank Steinbrücker received his Bachelor's degree in 2007 and his Master's degree in Computer Science in 2008 at Saarland University (Germany). Since September 2008 he is a Ph.D. student in the Research Group for Computer Vision, Image Processing and Pattern Recognition at the University of Bonn headed by Professor Daniel Cremers.

Visual Odometry

At ICCV 2011 we published a method for getting a camera pose estimation from RGBD-Images. In the video below, the Kinect camera is moving in a static scene and the camera poses are being accurately estimated.

Dense Mapping of large RGB-D Sequences

In our publication at ICCV 2013 I describe a method for the volumetric fusion of large RGB-D sequences. The video below shows the mesh visualization of our office floor, a scene computed from more than 24.000 RGB-D images captured with the Asus Xtion sensor. The reconstruction run at more than 200 Hz on a GTX680. The finest resolution was 5mm and the entire scene fit into approximately 2.5 GB of GPU RAM, including color.

While the method published at ICCV 2013 required a GPU to run in real-time, in our paper published at ICRA 2014, we demonstrated that the mapping part of dense volumetric RGB-D image fusion also works on a single standard CPU core at camera speed. Furthermore, we describe a method for incrementally extracting mesh surfaces from the volumetric data in approximately 1 Hz on a separate CPU core. In comparison to ray-casting visualization methods, surface meshes have the benefit that the visualization is view-independent. Therefore, this method is applicable for transmitting the visualization from an embedded system to a base-station. The video below demonstrates our method published at ICRA 2014.

Publications


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Book Chapters
2013
[]Moment Constraints in Convex Optimization for Segmentation and Tracking (M. Klodt, F. Steinbruecker and D. Cremers), Chapter in Advanced Topics in Computer Vision, Springer, 2013.  [bibtex] [pdf]
Conference and Workshop Papers
2014
[]Volumetric 3D Mapping in Real-Time on a CPU (F. Steinbruecker, J. Sturm and D. Cremers), In International Conference on Robotics and Automation (ICRA), 2014.  [bibtex] [pdf]
2013
[]Large-Scale Multi-Resolution Surface Reconstruction from RGB-D Sequences (F. Steinbruecker, C. Kerl, J. Sturm and D. Cremers), In IEEE International Conference on Computer Vision (ICCV), 2013.  [bibtex] [pdf]
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]
2009
[]Advanced Data Terms for Variational Optic Flow Estimation (F. Steinbruecker, T. Pock and D. Cremers), In Proceedings Vision, Modeling and Visualization (VMV), 2009.  [bibtex] [pdf]
[]Large Displacement Optical Flow Computation without Warping (F. Steinbruecker, T. Pock and D. Cremers), In IEEE International Conference on Computer Vision (ICCV), 2009.  [bibtex] [pdf]
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Rechte Seite

Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:

News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

More