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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)
1 Motivation Recovering 3D information from a single moving camera is a widely studied field in the area of computer vision (e.g. [1]). Most of these Structure-from-Motion (SfM) approaches are based on so-called interest points (e.g. corners) in images, which can be accurately matched using powerful de-scriptors like SIFT [7]. Hence the output is usually a(More)
Traditional Structure-from-Motion (SfM) approaches work well for richly textured scenes with a high number of distinctive feature points. Since man-made environments often contain textureless objects, the resulting point cloud suffers from a low density in corresponding scene parts. The missing 3D information heavily affects all kinds of subsequent(More)
Extracting 3D information from a moving camera is traditionally based on interest point detection and matching. This is especially challenging in the built environment, where the number of distinctive interest points is naturally limited. While common Structure-from-Motion (SfM) approaches usually manage to obtain the correct camera poses, the number of(More)
The reversible phosphorylation of proteins on serine, threonine, and tyrosine residues is an important biological regulatory mechanism. In the context of genome integrity, signaling cascades driven by phosphorylation are crucial for the coordination and regulation of DNA repair. The two serine/threonine protein kinases ataxia telangiectasia-mutated (ATM)(More)
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