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

Author(s):  
Simone Melzi ◽  
Riccardo Spezialetti ◽  
Federico Tombari ◽  
Michael M. Bronstein ◽  
Luigi Di Stefano ◽  
...  
2011 ◽  
Vol 27 (11) ◽  
pp. 991-1004 ◽  
Author(s):  
M. Attene ◽  
S. Marini ◽  
M. Spagnuolo ◽  
B. Falcidieno

Author(s):  
Adrian Ion ◽  
Nicole M. Artner ◽  
Gabriel Peyre ◽  
Salvador B. Lopez Marmol ◽  
Walter G. Kropatsch ◽  
...  

Author(s):  
Manuele Bicego ◽  
Stefano Danese ◽  
Simone Melzi ◽  
Umberto Castellani

Author(s):  
Jiangping Wang ◽  
Kai Ma ◽  
Vivek Kumar Singh ◽  
Thomas Huang ◽  
Terrence Chen

2015 ◽  
Vol 3 (11) ◽  
pp. 6651-6688
Author(s):  
J. Yu ◽  
G. Wang

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.


Author(s):  
Jingsheng Zhang ◽  
Shana Smith

To achieve effective 3D shape retrieval, there is a crucial need for efficient shape matching methods. This paper introduces a new method for 3D shape matching, which uses a simplified octree representation of 3D mesh models. The simplified octree representation was developed to improve time and space efficiency over prior representations. The proposed method also stores octree information in extensible markup language format, rather than in a new proprietary data file type, to facilitate comparing models over the Internet.


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