J
Johannes Schneider
Researcher at University of Bonn
Publications - 9
Citations - 207
Johannes Schneider is an academic researcher from University of Bonn. The author has contributed to research in topics: Bundle adjustment & Stereo camera. The author has an hindex of 8, co-authored 9 publications receiving 183 citations.
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Proceedings ArticleDOI
Multimodal obstacle detection and collision avoidance for micro aerial vehicles
TL;DR: A lightweight 3D laser scanner and visual obstacle detection using wide-angle stereo cameras and a fast reactive collision avoidance approach for safe operation in the vicinity of structures like buildings or vegetation are implemented.
Proceedings ArticleDOI
Fast and effective online pose estimation and mapping for UAVs
Johannes Schneider,Christian Eling,Lasse Klingbeil,Heiner Kuhlmann,Wolfgang Förstner,Cyrill Stachniss +5 more
TL;DR: An effective system for online pose and simultaneous map estimation designed for light-weight UAVs that has been implemented and thoroughly tested on a 5 kg copter and yields accurate and reliable pose estimation at high frequencies is proposed.
Journal ArticleDOI
Incremental real-time bundle adjustment for multi-camera systems with points at infinity
TL;DR: This paper presents a concept and first experiments on a keyframe-based incremental bundle adjustment for real-time structure and motion estimation in an unknown scene using the software iSAM2 for sparse nonlinear incremental optimization, which is highly efficient through incremental variable reordering and fluid relinearization.
Journal ArticleDOI
Bundle Adjustment for Multi-Camera Systems with Points at Infinity
TL;DR: A novel approach for a rigorous bundle adjustment for omnidirectional and multi-view cameras is presented, which enables an efficient maximum-likelihood estimation with image and scene points at infinity.
Journal ArticleDOI
Cloud photogrammetry with dense stereo for fisheye cameras
Christoph Beekmans,Johannes Schneider,Thomas Läbe,Martin Lennefer,Cyrill Stachniss,Clemens Simmer +5 more
TL;DR: An epipolar rectification model designed for fisheye cameras is examined, which allows the use of efficient out-of-the-box dense matching algorithms designed for classical pinhole-type cameras to search for correspondence information at every pixel in dense 3-D cloud reconstruction above an area of 10 × 10 km2.