scholarly journals A Comparative Study of Weighting Methods for Local Reference Frame

2020 ◽  
Vol 10 (9) ◽  
pp. 3223
Author(s):  
Wuyong Tao ◽  
Xianghong Hua ◽  
Kegen Yu ◽  
Ruisheng Wang ◽  
Xiaoxing He
Keyword(s):  
Reference Frame ◽  
Research Area ◽  
Density Variation ◽  
3D Registration ◽  
Local Reference Frame ◽  
Local Shape ◽  
Advantages And Disadvantages ◽  
Local Reference ◽  
Local Shape Descriptors ◽  
Weighting Methods

In the field of photogrammetric engineering, computer vision, and graphics, local shape description is an active research area. A wide variety of local shape descriptors (LSDs) have been designed for different applications, such as shape retrieval, object recognition, and 3D registration. The local reference frame (LRF) is an important component of the LSD. Its repeatability and robustness directly influence the descriptiveness and robustness of the LSD. Several weighting methods have been proposed to improve the repeatability and robustness of the LRF. However, no comprehensive comparison has been implemented to evaluate their performance under different data modalities and nuisances. In this paper, we focus on the comparison of weighting methods by using six datasets with different data modalities and application contexts. We evaluate the repeatability of the LRF under different nuisances, including occlusion, clutter, partial overlap, varying support radii, Gaussian noise, shot noise, point density variation, and keypoint localization error. Through the experiments, the traits, advantages, and disadvantages of weighting methods are summarized.

scholarly journals Quintuple Local Coordinate Images for Local Shape Description

2020 ◽  
Vol 86 (2) ◽  
pp. 121-132 ◽  
Author(s):  
Wuyong Tao ◽  
Xianghong Hua ◽  
Ruisheng Wang ◽  
Dong Xu
Keyword(s):  
Spatial Information ◽  
Density Variation ◽  
Feature Representation ◽  
Data Sets ◽  
Local Shape ◽  
Noise Point ◽  
Point Density ◽  
Local Reference ◽  
Local Shape Descriptors ◽  
Partial Overlap

Owing to poor descriptiveness, weak robustness, and high computation complexity of local shape descriptors (<small>LSDs</small>), point-cloud registration in the case of partial overlap and object recognition in a cluttered environment are still challeng- ing tasks. For this purpose, an <small>LSD</small> is developed in this article by proposing a new local reference frame (<small>LRF</small>) method and designing a novel feature representation. In the <small>LRF</small> method, two weighting methods are applied to obtain robustness to noise, point-density variation, and incomplete shape. Additionally, a vector representation is calculated to disambiguate the sign of the x-axis. The feature representation encodes the local information by generating the local coordinate images from five views. Thus, more geometric and spatial information is included in the descriptor. Finally, the performance of the <small>LRF</small> method and the <small>LSD</small> is evaluated on several popular data sets. The experimental results demonstrate well that the <small>LRF</small> is robust to noise, point-density variation, and incomplete shape, and the <small>LSD</small> holds strong robustness, superior descriptiveness, and high computational efficiency.

scholarly journals GPS derived ground motions (2005–2014) within the Gulf of Mexico region referred to a stable Gulf of Mexico reference frame

2015 ◽  
Vol 3 (11) ◽  
pp. 6651-6688
Author(s):  
J. Yu ◽  
G. Wang
Keyword(s):  
Gulf Of Mexico ◽  
Reference Frame ◽  
Mexico City ◽  
Ground Motions ◽  
Local Reference Frame ◽  
Local Reference ◽  
Houston Area ◽  
Gps Observations ◽  
Southeastern Louisiana

Abstract. This study investigates current ground motions derived from the GPS geodesy infrastructure in the Gulf of Mexico region. The positions and velocity vectors of 161 continuous GPS (CGPS) stations are presented with respect to a newly established local reference frame, the Stable Gulf of Mexico Reference Frame (SGOMRF). Thirteen long-term (> 5 years) CGPS are used to realize the local reference frame. The root-mean-square (RMS) of the velocities of the 13 SGOMRF reference stations achieves 0.2 mm yr−1 in the horizontal and 0.3 mm yr−1 in the vertical directions. GPS observations presented in this study indicate significant land subsidence in the coastal area of southeastern Louisiana, the greater Houston metropolitan area, and two cities in Mexico (Aguascalientes and Mexico City). The most rapid subsidence is recorded at the Mexico City International airport, which is up to 26.6 cm yr−1 (2008–2014). Significant spatial variation of subsidence rates is observed in both Mexico City and the Houston area. The overall subsidence rate in the Houston area is decreasing. GPS observations in southeastern Louisiana indicate minor (4.0–6.0 mm yr−1) but consistent subsidence over time and space. This poses a potential threat to the safety of costal infrastructure in the long-term.

scholarly journals GPS-derived ground deformation (2005–2014) within the Gulf of Mexico region referred to a stable Gulf of Mexico reference frame

2016 ◽  
Vol 16 (7) ◽  
pp. 1583-1602 ◽  
Author(s):  
Jiangbo Yu ◽  
Guoquan Wang
Keyword(s):  
Gulf Of Mexico ◽  
Reference Frame ◽  
Mexico City ◽  
Ground Deformation ◽  
Local Reference Frame ◽  
Subsidence Rate ◽  
Local Reference ◽  
Houston Area ◽  
Southeastern Louisiana

Abstract. This study investigates current ground deformation derived from the GPS geodesy infrastructure in the Gulf of Mexico region. The positions and velocity vectors of 161 continuous GPS (CGPS) stations are presented with respect to a newly established local reference frame, the Stable Gulf of Mexico Reference Frame (SGOMRF). Thirteen long-term (> 5 years) CGPS are used to realize the local reference frame. The root mean square (RMS) of the velocities of the 13 SGOMRF reference stations achieves 0.2 mm yr−1 in the horizontal and 0.3 mm yr−1 in the vertical directions. GPS observations presented in this study indicate significant land subsidence in the coastal area of southeastern Louisiana, the greater Houston metropolitan area, and two cities in Mexico (Aguascalientes and Mexico City). The most rapid subsidence is recorded at the Mexico City International airport, which is up to 26.6 cm yr−1 (2008–2014). Significant spatial variation of subsidence rates is observed in both Mexico City and the Houston area. The overall subsidence rate in the Houston area is decreasing. The subsidence rate in southeastern Louisiana is relatively smaller (4.0–6.0 mm yr−1) but tends to be steady over time. This poses a potential threat to the safety of coastal infrastructure in the long-term.

GFrames: Gradient-Based Local Reference Frame for 3D Shape Matching

2019 ◽  
Author(s):  
Simone Melzi ◽  
Riccardo Spezialetti ◽  
Federico Tombari ◽  
Michael M. Bronstein ◽  
Luigi Di Stefano ◽  
...  
Keyword(s):  
Reference Frame ◽  
Shape Matching ◽  
Local Reference Frame ◽  
3D Shape ◽  
Local Reference ◽  
Gradient Based ◽  
3D Shape Matching

scholarly journals Pointing Errors in Non-Metric Virtual Environments

2018 ◽  
Author(s):  
Alexander Muryy ◽  
Andrew Glennerster
Keyword(s):  
Virtual Reality ◽  
Virtual Environments ◽  
Reference Frame ◽  
Cognitive Map ◽  
Immersive Virtual Reality ◽  
Local Reference Frame ◽  
Human Navigation ◽  
Pointing Errors ◽  
Representation Of Space ◽  
Local Reference

AbstractThere have been suggestions that human navigation may depend on representations that have no metric, Euclidean interpretation but that hypothesis remains contentious. An alternative is that observers build a consistent 3D representation of space. Using immersive virtual reality, we measured the ability of observers to point to targets in mazes that had zero, one or three ‘wormholes’ – regions where the maze changed in configuration (invisibly). In one model, we allowed the configuration of the maze to vary to best explain the pointing data; in a second model we also allowed the local reference frame to be rotated through 90, 180 or 270 degrees. The latter model outperformed the former in the wormhole conditions, inconsistent with a Euclidean cognitive map.

A local reference frame for describing the proximal human femur: application in clinical settings

2013 ◽  
Vol 43 (3) ◽  
pp. 323-329 ◽  
Author(s):  
Milad Masjedi ◽  
Charison Tay ◽  
Simon J. Harris ◽  
Justin P. Cobb
Keyword(s):  
Reference Frame ◽  
Clinical Settings ◽  
Local Reference Frame ◽  
Human Femur ◽  
Local Reference
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