Explore chapters and articles related to this topic
Working Principle of GNSS
Published in Basudeb Bhatta, Global Navigation Satellite Systems, 2021
Triangulation is used for many purposes, including surveying, navigation, metrology, astrometry, binocular vision, model rocketry, establishing the direction of weapons, etc. Many of these applications involve the solution of large meshes of triangles, with hundreds or even thousands of observations.
Skeleton Extraction of Routing Topology in UAV Networks
Published in Fei Hu, Xin-Lin Huang, DongXiu Ou, UAV Swarm Networks, 2020
Zhe Chu, Lin Zhang, Zhijing Ye, Fei Hu, Bao Ke
The second step is to find the coordination of each surface node. Note that the UAV network we target here is GPS free, which means that we can only find the approximate, relative coordinates of each boundary node. The real Euclidean distance between two adjacent sensors can be approximately measured by received signal strength (RSS) or time difference of arrival (TDOA), whereas the real distance between two remote nodes is often estimated by their shortest path [3]. In 2D networks, it is sufficient to estimate the approximate relative coordinates of each node via mathematical geometry, such as trilateration theory. GPS also uses such a theory to compute the coordinate, but it has accurate distance measurement via satellite signals. Triangulation is a popular location measurement method by using either angles or distances.
Glossary of Computer Vision Terms
Published in Edward R. Dougherty, Digital Image Processing Methods, 2020
Robert M. Haralick, Linda G. Shapiro
Triangulation refers to the process of determining the (x, y, z) coordinates of a 3D point from the observed position of two perspective projections of the point. The centers of perspectivity and the perspective projection planes are assumed known.
Architecture, biometrics, and virtual environments triangulation: a research review
Published in Architectural Science Review, 2022
Despite the fact that methodical triangulation is the most popular, there are four forms of triangulation: Data triangulation, investigator triangulation, theoretical triangulation and methodological triangulation (Denzin 2006). According to Webb et al. (1966), triangulation is the convergence of multiple methods on the same research question to corroborate evidence from several different angles. Triangulation in this paper is the convergence of architectural design evaluation, biometric recording, and VE simulation methods on the research question to verify evidence from different sources. The primary purpose of the triangulation method is exploratory, generative, and evaluative, making it capable for early exploration and concept generation for testing and evaluation (Hanington and Martin 2012). Biometrics, architecture and VE triangulation can improve the understanding of human behaviour in response to the built environment. The triangulation investigates beneficial outcomes of human neurofeedback for design suggestions. In this context, this section elucidates the concept of design evaluation for human well-being, investigates the principal available methodologies for non-invasive human neurological response monitoring, and explains the visual simulator specification used for virtual environments.
Uncertainty quantification in digital image correlation for experimental evaluation of deep learning based damage diagnostic
Published in Structure and Infrastructure Engineering, 2021
Nur Sila Gulgec, Martin Takáč, Shamim N. Pakzad
The matching process of 3D-DIC consists of two steps: stereo and temporal matching (Tang, Liang, Xiao, & Guo, 2012). The stereo tracking requires matching of the subsets in the images taken by the left and right cameras; whereas, temporal matching aims to track the subsets in the reference and deformed images captured by the same camera as in 2D-DIC (Pan et al., 2008). After the matching of all subsets in the images, 3D coordinates of all the points are obtained through a triangulation method. Triangulation utilises the information obtained from sensor calibration to determine the spatial coordinates of the corresponding image points (Pan et al., 2010). During calibration, several images are captured from different angles and focal lengths of the specimen to track the rotations and translations.
2D sound source position estimation using microphone arrays and its application to a VR-based bird song analysis system
Published in Advanced Robotics, 2019
D. Gabriel, R. Kojima, K. Hoshiba, K. Itoyama, K. Nishida, K. Nakadai
Triangulation is a well known method for finding a point in space by forming triangles from azimuth lines estimated from known positions. Let us consider M microphone arrays with their known locations . Let be the azimuths estimated by , where and is the number of azimuths obtained from each microphone array in a given time frame. In each time frame the intersecting point between two azimuth lines is calculated by solving a system of two linear equations: with , and , easily obtained from known azimuth values and and microphone array positions and . To obtain intersecting points using all , this process is repeated for all combinations of different arrays.