Photogrammetry
Department for Photogrammetry
Nussallee 15
53115 Bonn
Phone:
Email:
Function:
+49.228.73-2904
(em.)
Room Number: 11

Fields of interest

  • Image Understanding
  • Pattern Recognition
  • Spatial Reasoning
  • Statistics
  • Geomatics

Curriculum Vitae (pdf)

to appear 4/2015: Buch: Photogrammetric Computer Vision (W. Förstner, B. P. Wrobel

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Private

Music

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Recent Publications

2014

Katja Herzog and Ribana Roscher and Markus Wieland and Anna Kicherer and Thomas Läbe and Wolfgang Förstner and Heiner Kuhlmann and Reinhard Töpfer, "Initial steps for high-throughput phenotyping in vineyards", VITIS - Journal of Grapevine Research., January, 2014. Vol. 53(1), pp. 1-8. 2014.

The evaluation of phenotypic characters of grape- vines is required directly in the vineyard and is strongly limited by time, costs and the subjectivity of person in charge. Sensor-based techniques are prerequisite to al- low non-invasive phenotyping of individual plant traits, to increase the quantity of object records and to reduce error variation. Thus, a Prototype-Image-Acquisition- System (PIAS) was developed for semi-automated cap- ture of geo-referenced RGB images in an experimental vineyard. Different strategies were tested for image in- terpretation using Matlab. The interpretation of imag- es from the vineyard with the real background is more practice-oriented but requires the calculation of depth maps. Images were utilised to verify the phenotyping results of two semi-automated and one automated pro- totype image interpretation framework. The semi-auto- mated procedures enable contactless and non-invasive detection of bud burst and quantification of shoots at an early developmental stage (BBCH 10) and enable fast and accurate determination of the grapevine berry size at BBCH 89. Depending on the time of image ac- quisition at BBCH 10 up to 94 % of green shoots were visible in images. The mean berry size (BBCH 89) was recorded non-invasively with a precision of 1 mm.

@article{Herzog2014Initial,
  author = {Herzog, Katja and Roscher, Ribana and Wieland, Markus and Kicherer,Anna and L\"abe, Thomas and F\"orstner, Wolfgang and Kuhlmann, Heiner and T\"opfer, Reinhard},
  title = {Initial steps for high-throughput phenotyping in vineyards},
  journal = {VITIS - Journal of Grapevine Research},
  year = {2014},
  volume = {53},
  number = {1},
  pages = {1--8}
}

Lasse Klingbeil and Matthias Nieuwenhuisen and Johannes Schneider and Christian Eling and David Droeschel and Dirk Holz and Thomas Läbe and Wolfgang Förstner and Sven Behnke and Heiner Kuhlmann, "Towards Autonomous Navigation of an UAV-based Mobile Mapping System", In 4th International Conference on Machine Control & Guidance., March, 2014., pp. 136-147. 2014.

For situations, where mapping is neither possible from high altitudes nor from the ground, we are developing an autonomous micro aerial vehicle able to fly at low altitudes in close vicinity of obstacles. This vehicle is based on a MikroKopterTM octocopter platform (maximum total weight: 5kg), and contains a dual frequency GPS board, an IMU, a compass, two stereo camera pairs with fisheye lenses, a rotating 3D laser scanner, 8 ultrasound sensors, a real-time processing unit, and a compact PC for on-board ego-motion estimation and obstacle detection for autonomous navigation. A high-resolution camera is used for the actual mapping task, where the environment is reconstructed in three dimensions from images, using a highly accurate bundle adjustment. In this contribution, we describe the sensor system setup and present results from the evaluation of several aspects of the different subsystems as well as initial results from flight tests.

@inproceedings{Klingbeil2014Towards,
  author = {Klingbeil, Lasse and Nieuwenhuisen, Matthias and Schneider, Johannes and Eling, Christian and Droeschel, David and Holz, Dirk and L\"abe, Thomas and F\"orstner, Wolfgang and Behnke, Sven and Kuhlmann, Heiner},
  title = {Towards Autonomous Navigation of an UAV-based Mobile Mapping System},
  booktitle = {4th International Conference on Machine Control \& Guidance},
  year = {2014},
  pages = {136--147},
  url = {http://www.digibib.tu-bs.de/?docid=00056119}
}

Johannes Schneider and Wolfgang Förstner, "Real-time Accurate Geo-localization of a MAV with Omnidirectional Visual Odometry and GPS", In Proceedings of the 5th International Workshop on Computer Vision in Vehicle Technology (CVVT) with Special Session in Micro Aerial Vehicles (in conj. with ECCV), to appear. 2014.

This paper presents a system for direct geo-localization of a MAV in an unknown environment using visual odometry and precise real time kinematic (RTK) GPS information. Visual odometry is performed with a multi-camera system with four fisheye cameras that cover a wide field of view which leads to better constraints for localization due to long tracks and a better intersection geometry. Visual observations from the acquired image sequences are refined with a high accuracy on selected keyframes by an incremental bundle adjustment using the iSAM2 algorithm. The optional integration of GPS information yields long-time stability and provides a direct geo-referenced solution. Experiments show the high accuracy which is below 3 cm standard deviation in position.

@inproceedings{Schneider2014Accurate,
  author = {Schneider, Johannes and F\"orstner, Wolfgang},
  title = {Real-time Accurate Geo-localization of a MAV with Omnidirectional Visual Odometry and GPS},
  booktitle = {Proceedings of the 5th International Workshop on Computer Vision in Vehicle Technology (CVVT) with Special Session in Micro Aerial Vehicles (in conj. with ECCV), to appear},
  year = {2014},
  note = {to appear}
}

Johannes Schneider and Thomas Läbe and Wolfgang Förstner, "Real-Time Bundle Adjustment with an Omnidirectional Multi-Camera System and GPS", In Proceedings of the 4th International Conference on Machine Control & Guidance., pp. 98-103. 2014.

In this paper we present our system for visual odometry that performs a fast incremental bundle adjustment for real-time structure and motion estimation in an unknown scene. It is applicable to image streams of a calibrated multi-camera system with omnidirectional cameras. In this paper we use an autonomously flying octocopter that is equipped for visual odometry and obstacle detection with four fisheye cameras, which provide a large field of view. For real-time ego-motion estimation the platform is equipped, besides the cameras, with a dual frequency GPS board, an IMU and a compass. In this paper we show how we apply our system for visual odometry using the synchronized video streams of the four fisheye cameras. The position and orientation information from the GPS-unit and the inertial sensors can optionally be integrated into our system. We will show the obtained accuracy of pure odometry and compare it with the solution from GPS/INS.

@inproceedings{Schneider2014Realtime,
  author = {Schneider, Johannes and L\"abe, Thomas and F\"orstner, Wolfgang},
  title = {Real-Time Bundle Adjustment with an Omnidirectional Multi-Camera System and GPS},
  booktitle = {Proceedings of the 4th International Conference on Machine Control \& Guidance},
  year = {2014},
  pages = {98--103},
  url = {http://www.digibib.tu-bs.de/?docid=00056119}
}
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