We present a system for automatic reassembly of broken 3D solids. Given as input 3D digital models of the broken fragments, we analyze the geometry of the fracture surfaces to find a globally consistent reconstruction of the original object. Our reconstruction pipeline consists of a graph-cuts based segmentation algorithm for identifying potential fracture surfaces, feature-based robust global registration for pairwise matching of fragments, and simultaneous constrained local registration of multiple fragments. We develop several new techniques in the area of geometry processing, including the novel integral invariants for computing multi-scale surface characteristics, registration based on forward search techniques and surface consistency, and a non-penetrating iterated closest point algorithm. We illustrate the performance of our algorithms on a number of real-world examples.
Fascinating and elegant shapes may be folded from a single planar sheet of material without stretching, tearing or cutting, if one incorporates curved folds into the design. We present an optimization-based computational framework for design and digital reconstruction of surfaces which can be produced by curved folding. Our work not only contributes to applications in architecture and industrial design, but it also provides a new way to study the complex and largely unexplored phenomena arising in curved folding.
We present the sensor concept and first performance and accuracy assessment results of a novel lightweight topo-bathymetric laser scanner designed for integration on Unmanned Aerial Vehicles (UAVs), light aircraft, and helicopters. The instrument is particularly well suited for capturing river bathymetry in high spatial resolution as a consequence of (i) the low nominal flying altitude of 50-150 m above ground level resulting in a laser footprint diameter on the ground of typically 10-30 cm and (ii) the high pulse repetition rate of up to 200 kHz yielding a point density on the ground of approximately 20-50 points/m 2 . The instrument features online waveform processing and additionally stores the full waveform within the entire range gate for waveform analysis in post-processing. The sensor was tested in a real-world environment by acquiring data from two freshwater ponds and a 500 m section of the pre-Alpine Pielach River (Lower Austria). The captured underwater points featured a maximum penetration of two times the Secchi depth. On dry land, the 3D point clouds exhibited (i) a measurement noise in the range of 1-3 mm; (ii) a fitting precision of redundantly captured flight strips of 1 cm; and (iii) an absolute accuracy of 2-3 cm compared to terrestrially surveyed checkerboard targets. A comparison of the refraction corrected LiDAR point cloud with independent underwater checkpoints exhibited a maximum deviation of 7.8 cm and revealed a systematic depth-dependent error when using a refraction coefficient of n = 1.36 for time-of-flight correction. The bias is attributed to multi-path effects in the turbid water column (Secchi depth: 1.1 m) caused by forward scattering of the laser signal at suspended particles. Due to the high spatial resolution, good depth performance, and accuracy, the sensor shows a high potential for applications in hydrology, fluvial morphology, and hydraulic engineering, including flood simulation, sediment transport modeling, and habitat mapping.Remote Sens. 2020, 12, 986 2 of 28 UAV-based 3D data acquisition was first accomplished using light-weight camera systems, where advancements in digital photogrammetry and computer vision-enabled automatic data processing workflows for the derivation of dense 3D point clouds based on Structure-from-Motion (SfM) and Dense Image Matching (DIM). Due to advancements in UAV-platform technology and ongoing sensor miniaturization, today compact LiDAR sensors are increasingly integrated on both multi-copter and fixed-wing UAVs, enabling 3D mapping with unprecedented spatial resolution and accuracy. The tackled applications include topographic mapping, geomorphology, infrastructure inspection, environmental monitoring, forestry, and precision farming. While UAV-borne laser scanning (ULS) can already be considered state-of-the-art for mapping tasks above the water table, UAV-based bathymetric LiDAR still lacks behind, mainly due to payload restrictions.The established techniques for mapping bathymetry are single-or multi-beam echo sounding (SBES/MBES), incl...
Traditionally, ground‐penetrating radar (GPR) measurements for near‐surface geophysical archaeological prospection are conducted with single‐channel systems using GPR antennae mounted in a cart similar to a pushchair, or towed like a sledge behind the operator. The spatial data sampling of such GPR devices for the non‐invasive detection and investigation of buried cultural heritage was, with very few exceptions, at best 25 cm in cross‐line direction of the measurement. With two or three persons participating in the fieldwork, coverage rates between a quarter hectare and half a hectare per day are common, while frequently considerably smaller survey areas at often coarse measurement spacing have been reported. Over the past years, the advent of novel multi‐channel GPR antenna array systems has permitted an enormous increase in survey efficiency and spatial sampling resolution. Using GPR antenna arrays with up to 16 channels operating in parallel, in combination with automatic positioning solutions based on real‐time kinematic global navigation satellite systems or robotic total‐stations, it has become possible to map several hectares per day with as little as 8 cm cross‐line and 4 cm in‐line GPR trace spacing. While this dramatic increase in coverage rate has a positive effect on the reduction of costs of GPR surveys, and thus its more widespread use in archaeology, the increased spatial sampling for the first time allows for the high‐resolution imaging of relatively small archaeological structures, such as for example 25 cm wide post‐holes of Iron Age buildings or the brick pillars of Roman floor heating systems, permitting much improved archaeological interpretations of the collected data. We present the state‐of‐the‐art in large‐scale high‐resolution archaeological GPR prospection, covering hardware and software technology and fieldwork methodology as well as the closely related issues of processing and interpretation of the huge data sets. Application examples from selected European archaeological sites illustrate the progress made.
We present a system for automatic reassembly of broken 3D solids. Given as input 3D digital models of the broken fragments, we analyze the geometry of the fracture surfaces to find a globally consistent reconstruction of the original object. Our reconstruction pipeline consists of a graph-cuts based segmentation algorithm for identifying potential fracture surfaces, feature-based robust global registration for pairwise matching of fragments, and simultaneous constrained local registration of multiple fragments. We develop several new techniques in the area of geometry processing, including the novel integral invariants for computing multi-scale surface characteristics, registration based on forward search techniques and surface consistency, and a non-penetrating iterated closest point algorithm. We illustrate the performance of our algorithms on a number of real-world examples.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.