Christian Mostegel

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The main contribution of this paper is to bridge the gap between passive monocular SLAM and autonomous robotic systems. While passive monocular SLAM strives to reconstruct the scene and determine the current camera pose for any given camera motion, not every camera motion is equally suited for these tasks. In this work we propose methods to evaluate the(More)
In this paper we present an autonomous system for acquiring close-range high-resolution images that maximize the quality of a later-on 3D reconstruction with respect to coverage, ground resolution and 3D uncertainty. In contrast to previous work, our system uses the already acquired images to predict the confidence in the output of a dense multi-view stereo(More)
Learned confidence measures gain increasing importance for outlier removal and quality improvement in stereo vision. However, acquiring the necessary training data is typically a tedious and time consuming task that involves manual interaction, active sensing devices and/or synthetic scenes. To overcome this problem, we propose a new, flexible, and scalable(More)
In this talk, we showcase our outcome of the ambitious 3D-PITOTI project, which involves a multidisciplinary team of over 30 scientists from across Europe. The project focuses on the 3D aspect of recording, storing, processing and visualizing prehistoric rock art in the UNESCO World Heritage site in Valcamonica, Italy. The rock art was pecked into open-air(More)
In this paper we present a scalable approach for robustly computing a 3D surface mesh from multi-scale multi-view stereo point clouds that can handle extreme jumps of point density (in our experiments three orders of magnitude). The backbone of our approach is a combination of octree data partitioning, local Delaunay tetrahedralization and graph cut(More)
Figures 1, 2 and 3 are extensions to Fig. 5 in the original paper. These figures each show the sparsification curves for three frames of the KITTI2012 dataset [1]. To give a fair overview of good and bad examples, we ranked the frames depending on the benefit of our training data. As we ran multiple combinations of query algorithm (SGM [4] and SPS [6]) and(More)
An important focus of current research in the field of Micro Aerial Vehicles (MAVs) is to increase the safety of their operation in general unstructured environments. Especially indoors, where GPS cannot be used for localization, reliable algorithms for localization and mapping of the environment are necessary in order to keep an MAV airborne safely. In(More)
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