Self-correction of 3D reconstruction from multi-view stereo images

We present a self-correction approach to improving the 3D reconstruction of a multi-view 3D photogrammetry system. The self-correction approach has been able to repair the reconstructed 3D surface damaged by depth discontinuities. Due to self-occlusion, multi-view range images have to be acquired and integrated into a watertight nonredundant mesh model in order to cover the extended surface of an imaged object. The integrated surface often suffers from “dent” artifacts produced by depth discontinuities in the multi-view range images. In this paper we propose a novel approach to correcting the 3D integrated surface such that the dent artifacts can be repaired automatically. We show examples of 3D reconstruction to demonstrate the improvement that can be achieved by the self-correction approach. This self-correction approach can be extended to integrate range images obtained from alternative range capture devices

Topology verification for isosurface extraction

Journal ArticleThe broad goals of verifiable visualization rely on correct algorithmic implementations. We extend a framework for verification of isosurfacing implementations to check topological properties. Specifically, we use stratified Morse theory and digital topology to design algorithms which verify topological invariants. Our extended framework reveals unexpected behavior and coding mistakes in popular publicly available isosurface codes

Solid modelling for manufacturing: from Voelcker's boundary evaluation to discrete paradigms

Herb Voelcker and his research team laid the foundations of Solid Modelling, on which Computer-Aided Design is based. He founded the ambitious Production Automation Project, that included Constructive Solid Geometry (CSG) as the basic 3D geometric representation. CSG trees were compact and robust, saving a memory space that was scarce in those times. But the main computational problem was Boundary Evaluation: the process of converting CSG trees to Boundary Representations (BReps) with explicit faces, edges and vertices for manufacturing and visualization purposes. This paper presents some glimpses of the history and evolution of some ideas that started with Herb Voelcker. We briefly describe the path from “localization and boundary evaluation” to “localization and printing”, with many intermediate steps driven by hardware, software and new mathematical tools: voxel and volume representations, triangle meshes, and many others, observing also that in some applications, voxel models no longer require Boundary Evaluation. In this last case, we consider the current research challenges and discuss several avenues for further research.Project TIN2017-88515-C2-1-R funded by MCIN/AEI/10.13039/501100011033/FEDER‘‘A way to make Europe’’Peer ReviewedPostprint (published version

Procedural Generation of 2D Creatures

Käesoleva bakalaureusetöö raames arendati 2D olendite genereerimise süsteem ning selle süsteemi implementatsioon programmeerimiskeeles JavaScript. Süsteem tekitab mitmekesiseid olendeid ning nendega seotud andmed, sealhulgas skelett, geomeetria ja tekstuur. Bakalaureusetöö sisaldab süsteemi kirjeldust. Süsteemi iga sammu kohta on välja toodud tähtsamad põhimõtted ning seletatud mõned implementatsiooni üksikasjad.Töös analüüsitakse süsteemi tervikuna ning selle implementatsiooni. Tuuakse välja süsteemi probleemid ning nõrgad kohad ja mõõdetakse implementatsiooni jõudlust. Töö lõpus tuuakse välja süsteemi kasutusvõimalused ja võimalused selle edasi arendamiseks.The purpose of this thesis is the development of a system capable of generating a large variety of 2D creatures and their associated data, such as skeletons, meshes and textures. A JavaScript implementation of the system was developed for this thesis. This thesis contains a description of the developed system and a description of each step of the generation process and its principles with some additional notes about the specifics of the implementation.The creature generation system as a whole and its implementation are analysed and their advantages and drawbacks brought out. The performance of the implementation is also tested. Several possible improvements are proposed at the end of the thesis, as well as possible uses

CircNet: Meshing 3D Point Clouds with Circumcenter Detection

Reconstructing 3D point clouds into triangle meshes is a key problem in computational geometry and surface reconstruction. Point cloud triangulation solves this problem by providing edge information to the input points. Since no vertex interpolation is involved, it is beneficial to preserve sharp details on the surface. Taking advantage of learning-based techniques in triangulation, existing methods enumerate the complete combinations of candidate triangles, which is both complex and inefficient. In this paper, we leverage the duality between a triangle and its circumcenter, and introduce a deep neural network that detects the circumcenters to achieve point cloud triangulation. Specifically, we introduce multiple anchor priors to divide the neighborhood space of each point. The neural network then learns to predict the presences and locations of circumcenters under the guidance of those anchors. We extract the triangles dual to the detected circumcenters to form a primitive mesh, from which an edge-manifold mesh is produced via simple post-processing. Unlike existing learning-based triangulation methods, the proposed method bypasses an exhaustive enumeration of triangle combinations and local surface parameterization. We validate the efficiency, generalization, and robustness of our method on prominent datasets of both watertight and open surfaces. The code and trained models are provided at https://github.com/Ruitao-L/CircNet.Comment: accepted to ICLR202