Interactive registration method for 3D data fusion

2016 ◽  
Author(s):  
Arantxa Casanova ◽  
Alba Pujol-Miro ◽  
Javier Ruiz-Hidalgo ◽  
Josep R. Casas
Keyword(s):  
Data Fusion ◽  
Registration Method ◽  
3D Data

Ways-free registration method and its application in 3D data fusion

2001 ◽  
Author(s):  
Xinyu Kou ◽  
Zhong Wang ◽  
Mingzhou Chen ◽  
Shenghua Ye
Keyword(s):  
Data Fusion ◽  
Registration Method ◽  
3D Data

scholarly journals A High-Precision Registration Technology Based on Bundle Adjustment in Structured Light Scanning System

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Jianying Yuan ◽  
Qiong Wang ◽  
Xiaoliang Jiang ◽  
Bailin Li
Keyword(s):  
High Precision ◽  
Large Scale ◽  
Structured Light ◽  
Bundle Adjustment ◽  
Scanning System ◽  
Control Points ◽  
Registration Method ◽  
Global Control ◽  
3D Data ◽  
Structured Light Scanning

The multiview 3D data registration precision will decrease with the increasing number of registrations when measuring a large scale object using structured light scanning. In this paper, we propose a high-precision registration method based on multiple view geometry theory in order to solve this problem. First, a multiview network is constructed during the scanning process. The bundle adjustment method from digital close range photogrammetry is used to optimize the multiview network to obtain high-precision global control points. After that, the 3D data under each local coordinate of each scan are registered with the global control points. The method overcomes the error accumulation in the traditional registration process and reduces the time consumption of the following 3D data global optimization. The multiview 3D scan registration precision and efficiency are increased. Experiments verify the effectiveness of the proposed algorithm.

3D Data fusion for a mobile robot

2002 ◽  
Author(s):  
P. Mowforth ◽  
J. Shapiro
Keyword(s):  
Data Fusion ◽  
Mobile Robot ◽  
3D Data

A 2D/3D data fusion with range estimation on 2D sensor

2008 ◽  
Author(s):  
Matsuzaki Takashi ◽  
Kameda Hiroshi ◽  
Yamamoto Kazuhiko ◽  
Fuji Tatsuo ◽  
Maekawa Ryoji
Keyword(s):  
Data Fusion ◽  
Range Estimation ◽  
3D Data

Face recognition based on 2D and 3D data fusion

2015 ◽  
Vol 7 (1) ◽  
pp. 69
Author(s):  
Paweł Krotewicz ◽  
Wojciech Sankowski ◽  
Piotr Stefan Nowak
Keyword(s):  
Face Recognition ◽  
Data Fusion ◽  
3D Data ◽  
2D And 3D

scholarly journals Unveiling the third dimension in morphometry with automated quantitative volumetric computations

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lawrence R. Frank ◽  
Timothy B. Rowe ◽  
Doug M. Boyer ◽  
Lawrence M. Witmer ◽  
Vitaly L. Galinsky
Keyword(s):  
Computational Methods ◽  
Spherical Wave ◽  
Imaging Data ◽  
Data Repositories ◽  
Registration Method ◽  
3D Data ◽  
Volumetric Registration ◽  
Third Dimension ◽  
Data Collections

AbstractAs computed tomography and related technologies have become mainstream tools across a broad range of scientific applications, each new generation of instrumentation produces larger volumes of more-complex 3D data. Lagging behind are step-wise improvements in computational methods to rapidly analyze these new large, complex datasets. Here we describe novel computational methods to capture and quantify volumetric information, and to efficiently characterize and compare shape volumes. It is based on innovative theoretical and computational reformulation of volumetric computing. It consists of two theoretical constructs and their numerical implementation: the spherical wave decomposition (SWD), that provides fast, accurate automated characterization of shapes embedded within complex 3D datasets; and symplectomorphic registration with phase space regularization by entropy spectrum pathways (SYMREG), that is a non-linear volumetric registration method that allows homologous structures to be correctly warped to each other or a common template for comparison. Together, these constitute the Shape Analysis for Phenomics from Imaging Data (SAPID) method. We demonstrate its ability to automatically provide rapid quantitative segmentation and characterization of single unique datasets, and both inter-and intra-specific comparative analyses. We go beyond pairwise comparisons and analyze collections of samples from 3D data repositories, highlighting the magnified potential our method has when applied to data collections. We discuss the potential of SAPID in the broader context of generating normative morphologies required for meaningfully quantifying and comparing variations in complex 3D anatomical structures and systems.

scholarly journals THE GREAT WALL 3D DOCUMENTATION AND APPLICATION BASED ON MULTI-SOURCE DATA FUSION – A CASE STUDY OF NO.15 ENEMY TOWER OF THE NEW GUANGWU GREAT WALL

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 1465-1470
Author(s):  
W. Hua ◽  
Y. Qiao ◽  
M. Hou
Keyword(s):  
Data Fusion ◽  
Cultural Heritage ◽  
Structure Data ◽  
Laser Scanning ◽  
3D Structure ◽  
Terrestrial Laser Scanning ◽  
Heritage Sites ◽  
3D Data ◽  
Digital Documentation ◽  
Great Wall

Abstract. Laser scanning or photogrammetry are useful individual techniques for digital documentation of cultural heritage sites. However, these techniques are of limited usage if cultural heritage such as the Great Wall is in harsh geographical conditions. The Great Wall is usually built on the ridge with cliffs on both sides, so it is very difficult to construct scaffolding. Therefore, the three-dimensional (3D) data obtained from the traditional 3D laser scanning is not complete. As UAV cannot enter the enemy tower, the 3D structure data inside the enemy tower with unmanned aerial vehicle (UAV) photogrammetry is missing. In order to explore effective methods to completely collect the 3D data of cultural heritage under harsh geographical environment, this study focuses on establishing a 3D model and the associated digital documentation for the No.15 enemy tower of the New Guangwu Great Wall using a combination of terrestrial laser scanning and UAV photogrammetry. This paper proposes an integrated data collection method and reduces the layout of image control points using RTK-UAV technology, which improved work efficiency and reduced work risks as well. In this paper, the internal structure data of the Great Wall enemy tower was collected by laser scanning, the external structure data was collected by UAV photogrammetry, and data fusion was based on ICP algorithm. Finally, we obtained the complete and high quality 3D digital documentation of the Great Wall enemy tower, the data can be displayed digitally and help heritage experts complete the Great Wall's restoration. This study demonstrates the potential of integrating terrestrial laser scanning and UAV photogrammetry in 3D digital documentation of cultural heritage sites.

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