Parametric design for human body modeling by wireframe-assisted deep learning

Statistical learning of human body shape can be used for reconstructing or estimating body shapes from incomplete data, semantic parametric design, modifying images and videos, or simulation. A digital human body is normally represented in a high-dimensional space, and the number of vertices in a mesh is far larger than the number of human bodies in public available databases, which results in a model learned by Principle Component Analysis (PCA) can hardly reflect the true variety in human body shapes. While deep learning has been most successful on data with an underlying Euclidean or grid-like structure, the geometric nature of human body is non-Euclidean, it will be very challenging to perform deep learning techniques directly on such non-Euclidean domain. This paper presents a deep neural network (DNN) based hierarchical method for statistical learning of human body by using feature wireframe as one of the layers to separate the whole problem into smaller and more solvable sub-problems. The feature wireframe is a collection of feature curves which are semantically defined on the mesh of human body, and it is consistent to all human bodies. A set of patches can then be generated by clustering the whole mesh surface to separated ones that interpolate the feature wireframe. Since the surface is separated into patches, PCA only needs to be conducted on each patch but not on the whole surface. The spatial relationships between the semantic parameter, the wireframe and the patches are learned by DNN and linear regression respectively. An application of semantic parametric design is used to demonstrate the capability of the method, where the semantic parameters are linked to the feature wireframe instead of the mesh directly. Under this hierarchy, the feature wireframe acts like an agent between semantic parameters and the mesh, and also contains semantic meaning by itself. The proposed method of learning human body statistically with the help of feature wireframe is scalable and has a better quality

Study of medical image data transformation techniques and compatibility analysis for 3D printing

Various applications exist for additive manufacturing (AM) and reverse engineering (RE) within the medical sector. One of the significant challenges identified in the literature is the accuracy of 3D printed medical models compared to their original CAD models. Some studies have reported that 3D printed models are accurate, while others claim the opposite. This thesis aims to highlight the medical applications of AM and RE, study medical image reconstruction techniques into a 3D printable file format, and the deviations of a 3D printed model using RE. A case study on a human femur bone was conducted through medical imaging, 3D printing, and RE for comparative deviation analysis. In addition, another medical application of RE has been presented, which is for solid modelling. Segmentation was done using opensource software for trial and training purposes, while the experiment was done using commercial software. The femur model was 3D printed using an industrial FDM printer. Three different non-contact 3D scanners were investigated for the RE process. Post-processing of the point cloud was done in the VX Elements software environment, while mesh analysis was conducted in MeshLab. The scanning performance was measured using the VX Inspect environment and MeshLab. Both relative and absolute metrics were used to determine the deviation of the scanned models from the reference mesh. The scanners' range of deviations was approximately from -0.375 mm to 0.388 mm (range of about 0.763mm) with an average RMS of about 0.22 mm. The results showed that the mean deviation of the 3D printed model (based on 3D scanning) has an average range of about 0.46mm, with an average mean value of about 0.16 mm

Uncovering the specificities of CAD tools for industrial design with design theory – style models for generic singularity

International audienceAccording to some casual observers, computer-aided design (CAD) tools are very similar. These tools are used to design new artifacts in a digital environment; hence, they share typical software components, such as a computing engine and human-machine interface. However, CAD software is dedicated to specific professionals—such as engineers, three-dimensional (3D) artists, and industrial designers (IDs)—who claim that, despite their apparent similarities, CAD tools are so different that they are not substitutable. Moreover, CAD tools do not fully meet the needs of IDs. This paper aims at better characterizing CAD tools by taking into account their underlying design logic, which involves relying on recent advances in design theory. We show that engineering CAD tools are actually modeling tools that design a generic variety of products; 3D artist CAD tools not only design but immediately produce single digital artefacts; and ID CAD tools are neither a mix nor an hybridization of engineering CAD and 3D artist CAD tools but have their own logic, namely to create new conceptual models for a large variety of products, that is, the creation of a unique original style that leads to a generic singularity. Such tools are useful for many creative designers beyond IDs

CAD-Based Porous Scaffold Design of Intervertebral Discs in Tissue Engineering

With the development and maturity of three-dimensional (3D) printing technology over the past decade, 3D printing has been widely investigated and applied in the field of tissue engineering to repair damaged tissues or organs, such as muscles, skin, and bones, Although a number of automated fabrication methods have been developed to create superior bio-scaffolds with specific surface properties and porosity, the major challenges still focus on how to fabricate 3D natural biodegradable scaffolds that have tailor properties such as intricate architecture, porosity, and interconnectivity in order to provide the needed structural integrity, strength, transport, and ideal microenvironment for cell- and tissue-growth. In this dissertation, a robust pipeline of fabricating bio-functional porous scaffolds of intervertebral discs based on different innovative porous design methodologies is illustrated. Firstly, a triply periodic minimal surface (TPMS) based parameterization method, which has overcome the integrity problem of traditional TPMS method, is presented in Chapter 3. Then, an implicit surface modeling (ISM) approach using tetrahedral implicit surface (TIS) is demonstrated and compared with the TPMS method in Chapter 4. In Chapter 5, we present an advanced porous design method with higher flexibility using anisotropic radial basis function (ARBF) and volumetric meshes. Based on all these advanced porous design methods, the 3D model of a bio-functional porous intervertebral disc scaffold can be easily designed and its physical model can also be manufactured through 3D printing. However, due to the unique shape of each intervertebral disc and the intricate topological relationship between the intervertebral discs and the spine, the accurate localization and segmentation of dysfunctional discs are regarded as another obstacle to fabricating porous 3D disc models. To that end, we discuss in Chapter 6 a segmentation technique of intervertebral discs from CT-scanned medical images by using deep convolutional neural networks. Additionally, some examples of applying different porous designs on the segmented intervertebral disc models are demonstrated in Chapter 6

Rapid prototyping in early stages of architectural design

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1997.Includes bibliographical references (leaves 59).This thesis shows how architects can use Rapid Prototyping and what the advantages and disadvantages are in different manipulations of the tool. Chapter two attempts to chart a road map of the rapid prototyping media. The data were drawn from a number of first hand experiments conducted by the author as well as by colleagues in MIT School of Architecture and Harvard Graduate School of Design, and in actual practice. The whole research lies on the boundary between virtual and real, on physical prototyping from a digital file. Digital prototyping and manual prototyping are mentioned only as references. The research offers examples of manipulations of the media and conclude that rapid prototyping in preliminary stages of design is most appropriate when used in what is defined as Direct CAD (Computer Aided Design) with Direct CAM (Computer Aided Manufacturing). Furthermore, it identifies Semi -Direct CAD with Direct CAM as the manipulation most commonly used by architects. This manipulation is useful for presentation models but not very useful in early stages where ideas are less definite. This is the reason why rapid prototyping is generally considered inappropriate for early stages of architectural design. Instead of analyzing Rapid Prototyping technology this work concentrates on the process that involves Rapid Prototyping in new ways in design . It aims to stimulate the designer's imagination when thinking about three -dimensional design, design in motion and design at the interface between people and architecture, for example, chairs and kitchens. In this context Rapid Prototyping becomes merely a vehicle by which the architect explores the design process. Rapid Prototyping is proposed as a media to escape the limitation imposed by flat screen representation in what is defined as true three dimensional digital design. This technology was invented in engineering to increase design and manufacturing process performances.by Alvise Simondetti.M.S

High-performance geometric vascular modelling

Image-based high-performance geometric vascular modelling and reconstruction is an essential component of computer-assisted surgery on the diagnosis, analysis and treatment of cardiovascular diseases. However, it is an extremely challenging task to efficiently reconstruct the accurate geometric structures of blood vessels out of medical images. For one thing, the shape of an individual section of a blood vessel is highly irregular because of the squeeze of other tissues and the deformation caused by vascular diseases. For another, a vascular system is a very complicated network of blood vessels with different types of branching structures. Although some existing vascular modelling techniques can reconstruct the geometric structure of a vascular system, they are either time-consuming or lacking sufficient accuracy. What is more, these techniques rarely consider the interior tissue of the vascular wall, which consists of complicated layered structures. As a result, it is necessary to develop a better vascular geometric modelling technique, which is not only of high performance and high accuracy in the reconstruction of vascular surfaces, but can also be used to model the interior tissue structures of the vascular walls.This research aims to develop a state-of-the-art patient-specific medical image-based geometric vascular modelling technique to solve the above problems. The main contributions of this research are:- Developed and proposed the Skeleton Marching technique to reconstruct the geometric structures of blood vessels with high performance and high accuracy. With the proposed technique, the highly complicated vascular reconstruction task is reduced to a set of simple localised geometric reconstruction tasks, which can be carried out in a parallel manner. These locally reconstructed vascular geometric segments are then combined together using shape-preserving blending operations to faithfully represent the geometric shape of the whole vascular system.- Developed and proposed the Thin Implicit Patch method to realistically model the interior geometric structures of the vascular tissues. This method allows the multi-layer interior tissue structures to be embedded inside the vascular wall to illustrate the geometric details of the blood vessel in real world

A survey of free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle

The objective of this paper is to analyze free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle (UAV). Free software is the best choice when the reduction of production costs is necessary; nevertheless, the quality of free software may vary. This paper probably does not include all of the free software, but tries to describe or mention at least the most interesting programs. The first part of this paper summarizes the essential knowledge about UAVs, including the fundamentals of flight mechanics and aerodynamics, and the structure of a UAV system. The second section generally explains the modelling and simulation of a UAV. In the main section, more than 50 free programs for the design, analysis, modelling, and simulation of a UAV are described. Although the selection of the free software has been focused on small subsonic UAVs, the software can also be used for other categories of aircraft in some cases; e.g. for MAVs and large gliders. The applications with an historical importance are also included. Finally, the results of the analysis are evaluated and discussed—a block diagram of the free software is presented, possible connections between the programs are outlined, and future improvements of the free software are suggested. © 2015, CIMNE, Barcelona, Spain.Internal Grant Agency of Tomas Bata University in Zlin [IGA/FAI/2015/001, IGA/FAI/2014/006

Intelligent Generation of Graphical Game Assets: A Conceptual Framework and Systematic Review of the State of the Art

Procedural content generation (PCG) can be applied to a wide variety of tasks in games, from narratives, levels and sounds, to trees and weapons. A large amount of game content is comprised of graphical assets, such as clouds, buildings or vegetation, that do not require gameplay function considerations. There is also a breadth of literature examining the procedural generation of such elements for purposes outside of games. The body of research, focused on specific methods for generating specific assets, provides a narrow view of the available possibilities. Hence, it is difficult to have a clear picture of all approaches and possibilities, with no guide for interested parties to discover possible methods and approaches for their needs, and no facility to guide them through each technique or approach to map out the process of using them. Therefore, a systematic literature review has been conducted, yielding 200 accepted papers. This paper explores state-of-the-art approaches to graphical asset generation, examining research from a wide range of applications, inside and outside of games. Informed by the literature, a conceptual framework has been derived to address the aforementioned gaps

Towards Data-Driven Large Scale Scientific Visualization and Exploration

Technological advances have enabled us to acquire extremely large datasets but it remains a challenge to store, process, and extract information from them. This dissertation builds upon recent advances in machine learning, visualization, and user interactions to facilitate exploration of large-scale scientific datasets. First, we use data-driven approaches to computationally identify regions of interest in the datasets. Second, we use visual presentation for effective user comprehension. Third, we provide interactions for human users to integrate domain knowledge and semantic information into this exploration process. Our research shows how to extract, visualize, and explore informative regions on very large 2D landscape images, 3D volumetric datasets, high-dimensional volumetric mouse brain datasets with thousands of spatially-mapped gene expression profiles, and geospatial trajectories that evolve over time. The contribution of this dissertation include: (1) We introduce a sliding-window saliency model that discovers regions of user interest in very large images; (2) We develop visual segmentation of intensity-gradient histograms to identify meaningful components from volumetric datasets; (3) We extract boundary surfaces from a wealth of volumetric gene expression mouse brain profiles to personalize the reference brain atlas; (4) We show how to efficiently cluster geospatial trajectories by mapping each sequence of locations to a high-dimensional point with the kernel distance framework. We aim to discover patterns, relationships, and anomalies that would lead to new scientific, engineering, and medical advances. This work represents one of the first steps toward better visual understanding of large-scale scientific data by combining machine learning and human intelligence