Article
Environmental Sciences
Grzegorz Gabara, Piotr Sawicki
Summary: This paper presents a new benchmark dataset called CRBeDaSet, which is designed for evaluating close range, image-based 3D modeling and reconstruction techniques, and discusses the first empirical experiences of its use. The dataset includes a medium-sized building as the test object with diverse surface textures, as well as geodetic spatial control network and photogrammetric network data obtained from different instruments. The paper also describes and evaluates existing datasets and benchmarks.
Article
Computer Science, Information Systems
Safouane El Ghazouali, Alain Vissiere, Louis-Ferdinand Lafon, Mohamed-Lamjed Bouazizi, Hichem Nouira
Summary: Real-time inspection of large mechanical parts manufacturing using camera-based scanning systems is becoming more common in industry 4.0. The use of camera-based scanners requires a preliminary calibration process to estimate the intrinsic and extrinsic parameters. A machine learning approach combining polynomial approximation and particle swarm optimization is proposed for calibration. Synthetic and experimental evaluations show better convergence and performance compared to recent calibration methods.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Engineering, Multidisciplinary
J. Eastwood, R. K. Leach, S. Piano
Summary: This paper presents a method to autonomously remove the background from photogrammetric images, resulting in lower data processing times, reduced memory usage, and increased point density on the object surface. Experimental results show that the reconstructions with the background removed have a lower standard deviation in point to mesh distance, indicating improved measurement accuracy.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Forestry
Dimitrios Panagiotidis, Azadeh Abdollahnejad
Summary: The study compared methods for estimating stem volume accuracy from TLS data, revealing that the RANSAC and convex hull and H-TSP methods were more accurate. The study provides insight into the performance and accuracy of tested methods for tree-level stem volume estimation.
Review
Environmental Sciences
Efstathios Adamopoulos, Fulvio Rinaudo
Summary: The preservation of built cultural heritage is crucial in the face of various threats. Inspection and monitoring techniques help in understanding the factors putting heritage at risk, providing valuable insights for scientific investigations.
Article
Engineering, Biomedical
Lukas Burger, Lalith Sharan, Roger Karl, Christina Wang, Matthias Karck, Raffaele De Simone, Ivo Wolf, Gabriele Romano, Sandy Engelhardt
Summary: This study compares three commercially available depth sensors for use in surgical simulation, finding that the Intel D405 is most suited for close-range applications, while the Zed-Mini performs well in terms of temporal resolution and fill rate. The D405 shows potential for deformable registration of surfaces, but is not yet suitable for real-time tool tracking or surgical skill assessment.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2023)
Article
Optics
Seongjin Hong, Junaid ur Rehman, Yong-Su Kim, Young-Wook Cho, Seung-Woo Lee, Su-Yong Lee, Hyang-Tag Lim
Summary: This study investigates a strategy to achieve the best practical sensitivity by optimizing both mode-amplitudes of multi-mode N00N states and a split ratio of a multi-mode beam splitter, and experimentally demonstrates its effectiveness.
LASER & PHOTONICS REVIEWS
(2022)
Article
Optics
Lei Huang, Lukas Lienhard, Tianyi Wang, Francois Polack, Josep Nicolas, Steven Hulbert, Mourad Idir
Summary: We have developed the Multi-Pitch Nano-accuracy Surface Profiler (MPNSP) to characterize strongly curved X-ray mirrors for diffraction-limited soft X-ray focusing. The measurement process involves forward-and-backward scans along the tangential direction at multiple pitch angles. Our research and development aim to measure strongly curved X-ray mirrors with a large slope range while maintaining high measurement repeatability and self-consistency.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Valens Frangez, David Salido-Monzu, Andreas Wieser
Summary: This study investigates the deviations of distance measurements in high-end phase-based depth cameras and proposes a method to reduce these biases based on experimental data. The results show that the response to external temperature varies among cameras, but the distance biases are similar. The study also demonstrates the potential for batch error compensation.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Zhenshi Sun, Kun Liu, Junfeng Jiang, Tianhua Xu, Shuang Wang, Hairuo Guo, Tiegen Liu
Summary: An improved real-time positioning algorithm using maximum overlap discrete wavelet transform (MODWT) for long-range asymmetric fiber interferometer-based vibration sensors was proposed, which effectively removes noise, enhances endpoint detection precision, and improves time-frequency feature analysis. The algorithm demonstrated high efficiency and accuracy, with 98.2% of positioning errors within +/- 20m range at a sensing length of 82km and a mean processing time of 135ms. This proposed scheme has the potential to expand the applications of long-range vibration sensing systems.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Anna N. Popova, Vladimir S. Sukhomlinov, Aleksandr S. Mustafaev
Summary: The article presents a mathematical correction method for measuring spectral line intensity in the presence of the blooming effect using charge-coupled devices (CCDs). This method is applicable in atomic emission spectroscopy and helps expand the dynamic range of spark emission spectrometers while minimizing result distortions in high element concentrations.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Yuan Yu, Shuai Cui, Guijiang Yang, Luoqiu Xu, Yu Chen, Kaixiang Cao, Liang Wang, Yu Yu, Xinliang Zhang
Summary: We proposed and demonstrated a temperature sensor with both high resolution and large dynamic range based on simultaneous microwave photonic and optical measurements. By designing and fabricating two cascaded ring resonators (CRRs) with different temperature sensitivities and free spectral ranges (FSRs) as the sensing probe, and utilizing the ultrahigh-Q-factor microring in the CRR, we achieved a high temperature resolution with a microwave photonic notch filter (MPNF) and a large dynamic range with the optical transmission spectrum of the CRR. The combination of these two measurements realized the desired temperature sensor.
IEEE SENSORS JOURNAL
(2023)
Article
Automation & Control Systems
Davide Felice Redaelli, Sara Gonizzi Barsanti, Emilia Biffi, Fabio Alexander Storm, Giorgio Colombo
Summary: This paper compares the metrological behavior of low-cost and high-resolution digitizing devices for surveying human body parts, finding that fixed devices are more accurate than handheld ones, with Artec's Leo and Structure Sensor providing satisfactory levels of precision in orthopaedic applications. Handheld devices enable fast reconstruction of body parts and smooth motion results in lower deviation and higher reliability. The study demonstrates the suitability of handheld devices for orthopaedic applications in terms of speed, accuracy, and cost.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Environmental Sciences
S. Junttila, T. Holtta, N. Saarinen, V. Kankare, T. Yrttimaa, J. Hyyppa, M. Vastaranta
Summary: The study investigated the use of novel small hyperspectral sensors for non-destructive estimation of leaf water content. Results showed that the sensors captured variations in equivalent water thickness and relative water content, providing detailed insights into the dynamics of leaf water content. The study concluded that close-range hyperspectral spectroscopy can be a novel tool for continuous measurement of leaf water content and better understanding of plant responses to environmental conditions.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Geochemistry & Geophysics
Vlad-Cristian Miclea, Sergiu Nedevschi
Summary: Environment perception by computing depth is crucial for unmanned aerial vehicle (UAV) systems. However, due to limited payload capacity, most drones are equipped with a single camera, making it challenging to use depth perception methods based on LiDAR or stereo reconstruction. In this study, we propose a novel approach for monocular depth estimation (MDE) on aerial images using a customized CNN. Additionally, we introduce a learning-based correction method to improve accuracy at both short and long ranges. Our method demonstrates accurate and reliable depth estimation in various aerial scenarios, as shown on synthetic and real-life images captured by a drone.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
