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Schneider J.,University of Bonn | Forstner W.,Josef Schell Str. 34
Photogrammetrie, Fernerkundung, Geoinformation | Year: 2013

We present a calibration method for multi-view cameras that provides a rigorous maximum likelihood estimation of the mutual orientation of the cameras within a rigid multi-camera system. No calibration targets are needed, just a movement of the multi-camera system taking synchronized images of a highly textured and static scene. Multi-camera systems with non-overlapping views have to be rotated within the scene so that corresponding points are visible in different cameras at different times of exposure. By using an extended version of the projective collinearity equation all estimates can be optimized in one bundle adjustment where we constrain the relative poses of the cameras to be fixed. For stabilizing camera orientations - especially rotations - one should generally use points at the horizon within the bundle adjustment, which classical bundle adjustment programs are not capable of. We use a minimal representation of homogeneous coordinates for image and scene points which allows us to use images of omnidirectional cameras with single viewpoint like fisheye cameras and scene points at a large distance from the camera or even at infinity. We show results of our calibration method on (1) the omnidirectional multi-camera system Ladybug 3 from Point Grey, (2) a camera-rig with five cameras used for the acquisition of complex 3D structures and (3) a camera-rig mounted on a UAVconsisting offour fisheye cameras which provide a large field of view and which is used for visual odometry and obstacle detection in the project MoD (DFG-Project FOR 1505 "Mapping on Demand"). © 2013 E. Schweizerbart'sche Verlagsbuchhandlung, Stuttgart, Germany. Source


Wenzel S.,University of Bonn | Forstner W.,Josef Schell Str. 34
Photogrammetrie, Fernerkundung, Geoinformation | Year: 2013

Simplification of given polygons has attracted many researchers. Especially, finding circular and elliptical structures in images is relevant in many applications. Given pixel chains from edge detection, this paper proposes a method to segment them into straight line and ellipse segments. We propose an adaption of Douglas-Peucker's polygon simplification algorithm using circle segments instead of straight line segments and partition the sequence of points instead the sequence of edges. It is robust and decreases the complexity of given polygons better than the original algorithm. In a second step, we further simplify the poly-curve by merging neighbouring segments to straight line and ellipse segments. Merging is based on the evaluation of variation of entropy for proposed geometric models, which turns out as a combination of hypothesis testing and model selection. We demonstrate the results of circlePeucker as well as merging on several images of scenes with significant circular structures and compare them with the method of PATRAUCEAN et al. (2012). © 2013 E. Schweizerbart'sche Verlagsbuchhandlung, Stuttgart, Germany. Source


Schindler F.,University of Bonn | Forstner W.,Josef Schell Str. 34
Photogrammetrie, Fernerkundung, Geoinformation | Year: 2013

Data partitioning is a common problem in the field of point cloud and image processing applicable to segmentation and clustering. The general principle is to have high similarity of two data points, e.g. pixels or 3D points, within one region and low similarity among regions. This pair-wise similarity between data points can be represented in an attributed graph. In this article we propose a novel graph partitioning algorithm. It integrates a sampling strategy known as farthest point sampling with Dijkstra's algorithm for deriving a distance transform on a general graph, which does not need to be embedded in some space. According to the pair-wise attributes a Voronoi diagram on the graph is generated yielding the desired segmentation. We demonstrate our approach on various applications such as surface triangulation, surface segmentation, clustering and image segmentation. © 2013 E. Schweizerbart'sche Verlagsbuchhandlung, Stuttgart, Germany. Source


Forstner W.,Josef Schell Str. 34
Photogrammetrie, Fernerkundung, Geoinformation | Year: 2013

The paper gives an introduction into graphical models and their use in specifying stochastic models in geodesy and photogrammetry. Basic task in adjustment theory can intuitively be described and analysed using graphical models. The paper shows that geodetic networks and bundle adjustments can be interpreted as graphical models, both as Bayesian networks or as conditional random fields. Especially hidden Markov random fields and conditional random fields are demonstrated to be versatile models for parameter estimation and classification. © 2013 E. Schweizerbart'sche Verlagsbuchhandlung, Stuttgart, Germany. Source

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