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Autonomous navigation for large Unmanned Aerial Vehicles (UAVs) is fairly straightforward , as expensive sensors and monitoring devices can be employed. In contrast, obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAVs) which operate at low altitude in cluttered environments. Unlike large vehicles, MAVs can only carry very light(More)
— We examine a new method of façade segmentation in a multi-view scenario. A set of overlapping, thus redundant street-side images exists and each image shows multiple buildings. A semantic segmentation identifies primary areas in the image such as sky, ground, vegetation, and façade. Subsequently, repeated patterns are detected in image segments previous(More)
We present a novel system that is capable of generating live dense volumetric reconstructions based on input from a micro aerial vehicle. The distributed reconstruction pipeline is based on state-of-the-art approaches to visual SLAM and variational depth map fusion, and is designed to exploit the individual capabilities of the system components. Results are(More)
— Highly accurate localization of a micro aerial vehicle (MAV) with respect to a scene is important for a wide range of applications, in particular surveillance and inspection. Most existing approaches to visual localization focus on indoor environments, while such tasks require outdoor navigation. Within this work, we introduce a novel algorithm for(More)
The quality and completeness of 3D models obtained by Structure-from-Motion (SfM) heavily depend on the image acquisition process. If the user gets feedback about the reconstruction quality already during the acquisition , he can optimize this process. The goal of this paper is to support a user during image acquisition by giving online feedback of the(More)
We introduce a novel approach for separating and segmenting individual facades from streetside images. Our algorithm incorporates prior knowledge about arbitrarily shaped repetitive regions which are detected using intensity profile descriptors and a voting–based matcher. In the experiments we compare our approach to extended state–of–the–art matching(More)
We present a novel technique for the automatic alignment of Structure from Motion (SfM) models, acquired at ground level or by micro aerial vehicles, to an overhead Digital Surface Model (DSM) using GPS information. An additional refinement step based on the correlation of the DSM height map with the model height map corrects for the GPS localization(More)
Generating accurate 3D models of man-made objects and urban scenery from an image sequence is a challenging task. Traditional Structure-from-Motion (SfM) approaches often fail because of the high amount of untex-tured objects and wiry structures present. At the very least, these objects are poorly represented in the resulting point clouds. Since most(More)
The benefit of accurate camera calibration for recovering 3D structure from images is a well-studied topic. Recently 3D vision tools for end-user applications have become popular among large audiences, mostly unskilled in computer vision. This motivates the need for a flexible and user-centric camera calibration method which drastically releases the(More)