Exploring local regularities for 3D object recognition

In order to find better simplicity measurements for 3D object recognition, a new set of local regularities is developed and tested in a stepwise 3D reconstruction method, including localized minimizing standard deviation of angles(L-MSDA), localized minimizing standard deviation of segment magnitudes(L-MSDSM), localized minimum standard deviation of areas of child faces (L-MSDAF), localized minimum sum of segment magnitudes of common edges (L-MSSM), and localized minimum sum of areas of child face (L-MSAF). Based on their effectiveness measurements in terms of form and size distortions, it is found that when two local regularities: L-MSDA and L-MSDSM are combined together, they can produce better performance. In addition, the best weightings for them to work together are identified as 10% for L-MSDSM and 90% for L-MSDA. The test results show that the combined usage of L-MSDA and L-MSDSM with identified weightings has a potential to be applied in other optimization based 3D recognition methods to improve their efficacy and robustness

Parameter optimization and learning for 3D object reconstruction from line drawings.

Du, Hao.Thesis (M.Phil.)--Chinese University of Hong Kong, 2010.Includes bibliographical references (p. 61).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- 3D Reconstruction from 2D Line Drawings and its Applications --- p.1Chapter 1.2 --- Algorithmic Development of 3D Reconstruction from 2D Line Drawings --- p.3Chapter 1.2.1 --- Line Labeling and Realization Problem --- p.4Chapter 1.2.2 --- 3D Reconstruction from Multiple Line Drawings --- p.5Chapter 1.2.3 --- 3D Reconstruction from a Single Line Drawing --- p.6Chapter 1.3 --- Research Problems and Our Contributions --- p.12Chapter 2 --- Adaptive Parameter Setting --- p.15Chapter 2.1 --- Regularities in Optimization-Based 3D Reconstruction --- p.15Chapter 2.1.1 --- Face Planarity --- p.18Chapter 2.1.2 --- Line Parallelism --- p.19Chapter 2.1.3 --- Line Verticality --- p.19Chapter 2.1.4 --- Isometry --- p.19Chapter 2.1.5 --- Corner Orthogonality --- p.20Chapter 2.1.6 --- Skewed Facial Orthogonality --- p.21Chapter 2.1.7 --- Skewed Facial Symmetry --- p.22Chapter 2.1.8 --- Line Orthogonality --- p.24Chapter 2.1.9 --- Minimum Standard Deviation of Angles --- p.24Chapter 2.1.10 --- Face Perpendicularity --- p.24Chapter 2.1.11 --- Line Collinearity --- p.25Chapter 2.1.12 --- Whole Symmetry --- p.25Chapter 2.2 --- Adaptive Parameter Setting in the Objective Function --- p.26Chapter 2.2.1 --- Hill-Climbing Optimization Technique --- p.28Chapter 2.2.2 --- Adaptive Weight Setting and its Explanations --- p.29Chapter 3 --- Parameter Learning --- p.33Chapter 3.1 --- Construction of A Large 3D Object Database --- p.33Chapter 3.2 --- Training Dataset Generation --- p.34Chapter 3.3 --- Parameter Learning Framework --- p.37Chapter 3.3.1 --- Evolutionary Algorithms --- p.38Chapter 3.3.2 --- Reconstruction Error Calculation --- p.39Chapter 3.3.3 --- Parameter Learning Algorithm --- p.41Chapter 4 --- Experimental Results --- p.45Chapter 4.1 --- Adaptive Parameter Setting --- p.45Chapter 4.1.1 --- Use Manually-Set Weights --- p.45Chapter 4.1.2 --- Learn the Best Weights with Different Strategies --- p.48Chapter 4.2 --- Evolutionary-Algorithm-Based Parameter Learning --- p.49Chapter 5 --- Conclusions and Future Work --- p.53Bibliography --- p.5

3D reconstruction of curved objects from single 2D line drawings.

Wang, Yingze.Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.Includes bibliographical references (leaves 42-47).Abstract also in Chinese.Chapter 1 --- Introduction --- p.1Chapter 2 --- Related Work --- p.5Chapter 2.1 --- Line labeling and realization problem --- p.5Chapter 2.2 --- 3D reconstruction from multiple views --- p.6Chapter 2.3 --- 3D reconstruction from single line drawings --- p.7Chapter 2.3.1 --- Face identification from the line drawings --- p.7Chapter 2.3.2 --- 3D geometry reconstruction --- p.9Chapter 2.4 --- Our research topic and contributions --- p.13Chapter 3 --- Reconstruction of Curved Manifold Objects --- p.14Chapter 3.1 --- Assumptions and terminology --- p.14Chapter 3.2 --- Reconstruction of curved manifold objects --- p.17Chapter 3.2.1 --- Distinguishing between curved and planar faces --- p.17Chapter 3.2.2 --- Transformation of Line Drawings --- p.20Chapter 3.2.3 --- Regularities --- p.23Chapter 3.2.4 --- 3D Wireframe Reconstruction --- p.26Chapter 3.2.5 --- Generating Curved Faces --- p.28Chapter 3.2.6 --- The Complete 3D Reconstruction Algorithm --- p.33Chapter 4 --- Experiments --- p.35Chapter 5 --- Conclusions and Future Work --- p.40Chapter 5.1 --- Conclusions --- p.40Chapter 5.2 --- Future work --- p.40Bibliography --- p.4

A System for 3D Shape Estimation and Texture Extraction via Structured Light

Shape estimation is a crucial problem in the fields of computer vision, robotics and engineering. This thesis explores a shape from structured light (SFSL) approach using a pyramidal laser projector, and the application of texture extraction. The specific SFSL system is chosen for its hardware simplicity, and efficient software. The shape estimation system is capable of estimating the 3D shape of both static and dynamic objects by relying on a fixed pattern. In order to eliminate the need for precision hardware alignment and to remove human error, novel calibration schemes were developed. In addition, selecting appropriate system geometry reduces the typical correspondence problem to that of a labeling problem. Simulations and experiments verify the effectiveness of the built system. Finally, we perform texture extraction by interpolating and resampling sparse range estimates, and subsequently flattening the 3D triangulated graph into a 2D triangulated graph via graph and manifold methods

Scanning transmission electron microscopy tomography and 4D-stem applied to the study of chiral and self-assembled nanoparticles

Over recent years, advances in nanotechnology have led to an increased interest towards engineering nanomaterials with defined morphologies, for applications where the nanoparticle shape plays a significant role in processes, such as in catalysis, drug delivery and optics. Therefore, it is essential to resolve the 3D morphology and structure of these materials in order to gain understanding about their physical and chemical properties for further optimization. Following this line of research, this thesis explores a set of experiments that makes use of Scanning Transmission Electron Microscopy (STEM), incorporating both STEM tomography and 4D-STEM techniques. These techniques were used to investigate the origin of chiral shapes in Tellurium (Te) bipyramidal nanoparticles, where it was determined that the chiral geometries of the nanoparticles arise from growth mediated by screw dislocations rather than chiral ligands used in their synthesis. Gold (Au) nanoparticle self-assembled superlattices were studied by electron tomography and their lattice structure was investigated through determination of the 3D nanoparticle positions. The superlattices were found to have different crystalline structures for different molecular weights of their protective ligands. Finally, gold nanoparticles that seemed to have a twisted bipyramidal geometry were investigated through electron tomography. A model was built from the reconstructed cross-sections which supported the conclusion that the asymmetry in the shape resulted from the arrangement of the facets rather than a twist. The analyses performed in this thesis were custom-developed building upon general electron microscopy and mathematical concepts, enabling their application towards different systems and materials

Fast 3D Rotation Estimation of Fruits Using Spheroid Models

[EN] Automated fruit inspection using cameras involves the analysis of a collection of views of the same fruit obtained by rotating a fruit while it is transported. Conventionally, each view is analyzed independently. However, in order to get a global score of the fruit quality, it is necessary to match the defects between adjacent views to prevent counting them more than once and assert that the whole surface has been examined. To accomplish this goal, this paper estimates the 3D rotation undergone by the fruit using a single camera. A 3D model of the fruit geometry is needed to estimate the rotation. This paper proposes to model the fruit shape as a 3D spheroid. The spheroid size and pose in each view is estimated from the silhouettes of all views. Once the geometric model has been fitted, a single 3D rotation for each view transition is estimated. Once all rotations have been estimated, it is possible to use them to propagate defects to neighbor views or to even build a topographic map of the whole fruit surface, thus opening the possibility to analyze a single image (the map) instead of a collection of individual views. A large effort was made to make this method as fast as possible. Execution times are under 0.5 ms to estimate each 3D rotation on a standard I7 CPU using a single core.Albiol Colomer, AJ.; Albiol Colomer, A.; Sánchez De Merás, C. (2021). Fast 3D Rotation Estimation of Fruits Using Spheroid Models. Sensors. 21(6):1-24. https://doi.org/10.3390/s21062232S12421

Reconstruction of sculpture from its profiles with unknown camera positions

Profiles of a sculpture provide rich information about its geometry, and can be used for shape recovery under known camera motion. By exploiting correspondences induced by epipolar tangents on the profiles, a successful solution to motion estimation from profiles has been developed in the special case of circular motion. The main drawbacks of using circular motion alone, namely the difficulty in adding new views and part of the object always being invisible, can be overcome by incorporating arbitrary general views of the object and registering its new profiles with the set of profiles resulted from the circular motion. In this paper, we describe a complete and practical system for producing a three-dimensional (3-D) model from uncalibrated images of an arbitrary object using its profiles alone. Experimental results on various objects are presented, demonstrating the quality of the reconstructions using the estimated motion.published_or_final_versio

View generated database

This document represents the final report for the View Generated Database (VGD) project, NAS7-1066. It documents the work done on the project up to the point at which all project work was terminated due to lack of project funds. The VGD was to provide the capability to accurately represent any real-world object or scene as a computer model. Such models include both an accurate spatial/geometric representation of surfaces of the object or scene, as well as any surface detail present on the object. Applications of such models are numerous, including acquisition and maintenance of work models for tele-autonomous systems, generation of accurate 3-D geometric/photometric models for various 3-D vision systems, and graphical models for realistic rendering of 3-D scenes via computer graphics

Vision-assisted modeling for model-based video representations

Thesis (Ph. D.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1997.Includes bibliographical references (leaves 134-145).by Shawn C. Becker.Ph.D