3D reconstruction of point clouds using multi-view orthographic projections

Cataloged from PDF version of article.A method to reconstruct 3D point clouds using multi-view orthographic projections is examined. Point clouds are generated by means of a stochastic process. This stochastic process is designed to generate point clouds that mimic microcalcification formation in breast tissue. Point clouds are generated using a Gibbs sampler algorithm. Orthographic projections of point clouds from any desired orientation are generated. Volumetric intersection method is employed to perform the reconstruction from these orthographic projections. The reconstruction may yield erroneous reconstructed points. The types of these erroneous points are analyzed along with their causes and a performance measure based on linear combination is devised. Experiments have been designed to investigate the effect of the number of projections and the number of points to the performance of reconstruction. Increasing the number of projections and decreasing the number of points resulted in better reconstructions that are more similar to the original point clouds. However, it is observed that reconstructions do not improve considerably upon increasing the number of projections after some number. This method of reconstruction serves well to find locations of original points.Topçu, OsmanM.S

Doctor of Philosophy

dissertationVolumetric parameterization is an emerging field in computer graphics, where volumetric representations that have a semi-regular tensor-product structure are desired in applications such as three-dimensional (3D) texture mapping and physically-based simulation. At the same time, volumetric parameterization is also needed in the Isogeometric Analysis (IA) paradigm, which uses the same parametric space for representing geometry, simulation attributes and solutions. One of the main advantages of the IA framework is that the user gets feedback directly as attributes of the NURBS model representation, which can represent geometry exactly, avoiding both the need to generate a finite element mesh and the need to reverse engineer the simulation results from the finite element mesh back into the model. Research in this area has largely been concerned with issues of the quality of the analysis and simulation results assuming the existence of a high quality volumetric NURBS model that is appropriate for simulation. However, there are currently no generally applicable approaches to generating such a model or visualizing the higher order smooth isosurfaces of the simulation attributes, either as a part of current Computer Aided Design or Reverse Engineering systems and methodologies. Furthermore, even though the mesh generation pipeline is circumvented in the concept of IA, the quality of the model still significantly influences the analysis result. This work presents a pipeline to create, analyze and visualize NURBS geometries. Based on the concept of analysis-aware modeling, this work focusses in particular on methodologies to decompose a volumetric domain into simpler pieces based on appropriate midstructures by respecting other relevant interior material attributes. The domain is decomposed such that a tensor-product style parameterization can be established on the subvolumes, where the parameterization matches along subvolume boundaries. The volumetric parameterization is optimized using gradient-based nonlinear optimization algorithms and datafitting methods are introduced to fit trivariate B-splines to the parameterized subvolumes with guaranteed order of accuracy. Then, a visualization method is proposed allowing to directly inspect isosurfaces of attributes, such as the results of analysis, embedded in the NURBS geometry. Finally, the various methodologies proposed in this work are demonstrated on complex representations arising in practice and research

Search Me Knot, Render Me Knot: Embedding Search and Differentiable Rendering of Knots in 3D

We introduce the problem of knot-based inverse perceptual art. Given multiple target images and their corresponding viewing configurations, the objective is to find a 3D knot-based tubular structure whose appearance resembles the target images when viewed from the specified viewing configurations. To solve this problem, we first design a differentiable rendering algorithm for rendering tubular knots embedded in 3D for arbitrary perspective camera configurations. Utilizing this differentiable rendering algorithm, we search over the space of knot configurations to find the ideal knot embedding. We represent the knot embeddings via homeomorphisms of the desired template knot, where the homeomorphisms are parametrized by the weights of an invertible neural network. Our approach is fully differentiable, making it possible to find the ideal 3D tubular structure for the desired perceptual art using gradient-based optimization. We propose several loss functions that impose additional physical constraints, ensuring that the tube is free of self-intersection, lies within a predefined region in space, satisfies the physical bending limits of the tube material and the material cost is within a specified budget. We demonstrate through results that our knot representation is highly expressive and gives impressive results even for challenging target images in both single view as well as multiple view constraints. Through extensive ablation study we show that each of the proposed loss function is effective in ensuring physical realizability. To the best of our knowledge, we are the first to propose a fully differentiable optimization framework for knot-based inverse perceptual art. Both the code and data will be made publicly available.Comment: Work in progres

Doctor of Philosophy

dissertationWhile boundary representations, such as nonuniform rational B-spline (NURBS) surfaces, have traditionally well served the needs of the modeling community, they have not seen widespread adoption among the wider engineering discipline. There is a common perception that NURBS are slow to evaluate and complex to implement. Whereas computer-aided design commonly deals with surfaces, the engineering community must deal with materials that have thickness. Traditional visualization techniques have avoided NURBS, and there has been little cross-talk between the rich spline approximation community and the larger engineering field. Recently there has been a strong desire to marry the modeling and analysis phases of the iterative design cycle, be it in car design, turbulent flow simulation around an airfoil, or lighting design. Research has demonstrated that employing a single representation throughout the cycle has key advantages. Furthermore, novel manufacturing techniques employing heterogeneous materials require the introduction of volumetric modeling representations. There is little question that fields such as scientific visualization and mechanical engineering could benefit from the powerful approximation properties of splines. In this dissertation, we remove several hurdles to the application of NURBS to problems in engineering and demonstrate how their unique properties can be leveraged to solve problems of interest

Structure and motion estimation from apparent contours under circular motion

In this paper, we address the problem of recovering structure and motion from the apparent contours of a smooth surface. Fixed image features under circular motion and their relationships with the intrinsic parameters of the camera are exploited to provide a simple parameterization of the fundamental matrix relating any pair of views in the sequence. Such a parameterization allows a trivial initialization of the motion parameters, which all bear physical meaning. It also greatly reduces the dimension of the search space for the optimization problem, which can now be solved using only two epipolar tangents. In contrast to previous methods, the motion estimation algorithm introduced here can cope with incomplete circular motion and more widely spaced images. Existing techniques for model reconstruction from apparent contours are then reviewed and compared. Experiment on real data has been carried out and the 3D model reconstructed from the estimated motion is presented. © 2002 Elsevier Science B.V. All rights reserved.postprin

The hunters of humanity: creatures of horror in M. R. James's ghost stories

In his ghost stories, M.R. James disclosed the most irrational and fearful aspects of archaic demonology still haunting the modern world. He turns humans into prey species, hunted and haunted by repulsive insect- and spider-like demons. This paper offers a closer look at the creatures of horror and the recurrent theme of the hunt in James's ghost stories, viewing them in the context of Victorian evolutionary theories as well as traditional medieval beliefs. James's protagonists, unimaginative and unadventurous scholars, suddenly come face to face (or face to tentacle) with the enormity of the Universe and its non-human creatures as they invade and shatter the homely Edwardian world. From this perspective, James's works express the social and cultural fears of his generation

Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専