Team Fraundorfer

3D Vision, Vision for Robotics, Camera Drones

MAVMAP 3D reconstruction

Our research  focus is the the area of 3D computer vision including vision for robotics. A specific focus is on the topic of computer vision for camera drones, e.g. for aerial image processing or camera based navigation. We operate a variety of camera drones of different sizes and also operate an indoor flying arena.


BMVC 2017 Papers Accepted

July 24, 2017

Our papers "Combining Edge Images and Depth Maps for Robust Visual Odometry" [pdf] and "Plane-based Surface Regularization for Urban 3D Reconstruction" have been accepted and will be presented at this years' BMVC from 4th -7th September at Imperial College London.

Book Chapter: Computer Vision for MAVs!

March 20, 2017

The book "Computer Vision in Vehicle Technology: Land, Sea, and Air" is now available online and as printed book. It contains a chapter about "Computer Vision for MAVs" written by Friedrich Fraundorfer.

Awarded with Amazon gift !

March 1, 2017

Our team got awarded an Amazon gift for continuing our drone related research.

CVPR 2017 paper accepted!

February 28, 2017

Our paper has been accepted for publication at CVPR 2017!

Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity. Christian  Mostegel, Rudolf  Prettenthaler, Friedrich  Fraundorfer, Horst  Bischof.

3DV'16 paper accepted!

September 15, 2016

Our paper "Regularized 3D Modeling from Noisy Building Reconstructions" has been accepted for publication at 3DV'16! You can download a preprint version from [here].

Presentation at Ars Electronica Festival 2016

September 8-12, 2016


We presented our "Intelligent Search and Rescue Drone" in the Ars Electronica Festival 2016 - DroneLab, Linz, September 8-12, 2016. This was a great opportunity to approach the general public about civilian applications for drones and research made in the ICG (TU Graz). We used this opportunity to show our drone and the capabilities of our 3D resconstruction software, and to describe the Graz Griffins', our team, participation in the 2016 DJI Developer Challenge.

We qualified for DJI Developer Challenge Round 3!

August 9, 2016

Our team, the Graz Griffins is one of 10 teams which qualified for the 3rd round of the DJI Developer Challenge2016 (Team Listings)! Hence, we are allowed to participate in the final competition end of August at the Griffiss International Airport, Rome, New York, USA. [more]

CVPR Code Released!

May 19, 2016

We released our code of our CVPR paper, with which you can automatically generate training data for confidence learning in stereo vision. You can find it in the "Software" section.

CVPR and CVPRW paper accepted!

May 09, 2016

We are happy to announce that two of our papers got accepted to CVPR this year. One paper (Using Self-Contradiction to Learn Confidence Measures in Stereo Vision) will be presented at the main conference and a second paper (UAV-based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Prediction) at the CVPR workshop on Computer Vision in Vehicle Technology.

Journal paper accepted!

Apr 05, 2016

We are happy to announce that our journal paper got accepted at Computer Vision and Image Understanding (CVIU). More details can be found in the Publications section.

DJI Developer Challenge 2016!

Mar 29, 2016

Our team, the Graz
Griffins, has qualified to participate in the 2016 DJI Developer Challenge (see Challengers >> 1st round), among only 25 teams worldwide. The team consists of members from the IRT and the ICG, both institutes at the TU Graz. We will now receive our Developer Package, which includes the DJI Matrice M100 quadcopter equipped with the impressive DJI Guidance multipurpose sensing system, a Gimbal Zenmuse X3 camera and a DJI Manifold onboard computer!

VISAPP'16: Best Paper Award!

Mar 03, 2016

We won the Best Paper Award for our paper "Visual Odometry Based on Lines", which has been presented at this years VISAPP.

Direct Stereo Visual Odometry Based on Lines

Jan 22, 2016

Our new paper Direct Stereo Visual Odometry Based on Lines is now online, and can be found in the Publications section. It will be presented at this years VISAPP in Rome.

Key Facts

Research areas:

3D Computer Vision
Vision for Robotics
Drones (UAV's, MAV's)
3D Reconstruction from UAV images