Automatic Registration of RGBD Scans via Salient Directions

We address the problem of wide-baseline registration of RGB-D data, such as photo-textured laser scans without any artificial targets or prediction on the relative motion. Our approach allows to fully automatically register scans taken in GPS-denied environments such as urban canyon, industrial facilities or even indoors. We build upon image features which are plenty, localized well and much more discriminative than geometry features; however, they suffer from viewpoint distortions and request for normalization. We utilize the principle of salient directions present in the geometry and propose to extract (several) directions from the distribution of surface normals or other cues such as observable symmetries. Compared to previous work we pose no requirements on the scanned scene (like containing large textured planes) and can handle arbitrary surface shapes. Rendering the whole scene from these repeatable directions using an orthographic camera generates textures which are identical up to 2D similarity transformations. This ambiguity is naturally handled by 2D features and allows to find stable correspondences among scans. For geometric pose estimation from tentative matches we propose a fast and robust 2 point sample consensus scheme integrating an early rejection phase. We evaluate our approach on different challenging real world scenes

General Techniques for Approximate Incidences and Their Application to the Camera Posing Problem

We consider the classical camera pose estimation problem that arises in many computer vision applications, in which we are given n 2D-3D correspondences between points in the scene and points in the camera image (some of which are incorrect associations), and where we aim to determine the camera pose (the position and orientation of the camera in the scene) from this data. We demonstrate that this posing problem can be reduced to the problem of computing epsilon-approximate incidences between two-dimensional surfaces (derived from the input correspondences) and points (on a grid) in a four-dimensional pose space. Similar reductions can be applied to other camera pose problems, as well as to similar problems in related application areas. We describe and analyze three techniques for solving the resulting epsilon-approximate incidences problem in the context of our camera posing application. The first is a straightforward assignment of surfaces to the cells of a grid (of side-length epsilon) that they intersect. The second is a variant of a primal-dual technique, recently introduced by a subset of the authors [Aiger et al., 2017] for different (and simpler) applications. The third is a non-trivial generalization of a data structure Fonseca and Mount [Da Fonseca and Mount, 2010], originally designed for the case of hyperplanes. We present and analyze this technique in full generality, and then apply it to the camera posing problem at hand. We compare our methods experimentally on real and synthetic data. Our experiments show that for the typical values of n and epsilon, the primal-dual method is the fastest, also in practice

Single-Image Depth Prediction Makes Feature Matching Easier

Good local features improve the robustness of many 3D re-localization and multi-view reconstruction pipelines. The problem is that viewing angle and distance severely impact the recognizability of a local feature. Attempts to improve appearance invariance by choosing better local feature points or by leveraging outside information, have come with pre-requisites that made some of them impractical. In this paper, we propose a surprisingly effective enhancement to local feature extraction, which improves matching. We show that CNN-based depths inferred from single RGB images are quite helpful, despite their flaws. They allow us to pre-warp images and rectify perspective distortions, to significantly enhance SIFT and BRISK features, enabling more good matches, even when cameras are looking at the same scene but in opposite directions.Comment: 14 pages, 7 figures, accepted for publication at the European conference on computer vision (ECCV) 202

Cooling Rate Controlled Aging of a Co-Free Fe-Ni-Cr-Mo-Ti-Al Maraging Steel

Maraging steels are high-strength steels that are hardened by the formation of precipitates during an isothermal aging heat treatment. Depending on the aging temperature and time the cooling rate after holding can play a significant factor on the development of the microstructure and mechanical properties. This study seeks to show how the cooling time influences the precipitation hardening effect, austenite reversion and the development of hardness and impact toughness. The material was aged at a constant temperature using holding times of 0 h, 4 h and 15 h and cooled with different cooling rates resulting in cooling times of 7 h, 28 h and 56 h. The microstructure was characterized using a combination of electron backscatter diffraction, X-ray diffraction and atom probe tomography with cluster-based precipitate analysis. It is shown that the effect of the cooling time is strongly dependent on the holding time and that a longer cooling time can improve hardness and impact toughness

Cooling Rate Controlled Aging of a Co-Free Fe-Ni-Cr-Mo-Ti-Al Maraging Steel

Maraging steels are high-strength steels that are hardened by the formation of precipitates during an isothermal aging heat treatment. Depending on the aging temperature and time the cooling rate after holding can play a significant factor on the development of the microstructure and mechanical properties. This study seeks to show how the cooling time influences the precipitation hardening effect, austenite reversion and the development of hardness and impact toughness. The material was aged at a constant temperature using holding times of 0 h, 4 h and 15 h and cooled with different cooling rates resulting in cooling times of 7 h, 28 h and 56 h. The microstructure was characterized using a combination of electron backscatter diffraction, X-ray diffraction and atom probe tomography with cluster-based precipitate analysis. It is shown that the effect of the cooling time is strongly dependent on the holding time and that a longer cooling time can improve hardness and impact toughness