Separation of line drawings based on split faces for 3D object reconstruction

© 2014 IEEE. Reconstructing 3D objects from single line drawings is often desirable in computer vision and graphics applications. If the line drawing of a complex 3D object is decomposed into primitives of simple shape, the object can be easily reconstructed. We propose an effective method to conduct the line drawing separation and turn a complex line drawing into parametric 3D models. This is achieved by recursively separating the line drawing using two types of split faces. Our experiments show that the proposed separation method can generate more basic and simple line drawings, and its combination with the example-based reconstruction can robustly recover wider range of complex parametric 3D objects than previous methods.This work was supported by grants from Science, Industry, Trade, and Information Technology Commission of Shenzhen Municipality (No. JC201005270378A), Guangdong Innovative Research Team Program (No. 201001D0104648280), Shenzhen Basic Research Program (JCYJ20120617114614438, JC201005270350A, JCYJ20120903092050890), Scientific Research Fund of Hunan Provincial Education Department (No. 13C073), Industrial Technology Research and Development Program of Hengyang Science and Technology Bureau (No.2013KG75), and the Construct Program of the Key Discipline in Hunan Provinc

MeasureIt-ARCH: A Tool for Facilitating Architectural Design in the Open Source Software Blender

This thesis discusses the design and synthesis of MeasureIt-ARCH, a GNU GPL licensed software add-on developed by the author in order to add functionality to the Open Source 3D modeling software Blender that facilitates the creation of architectural drawings. MeasureIt-ARCH adds to Blender simple tools to dimension and annotate 3D models, as well as basic support for the definition and drawing of line work. These tools for the creation of dimensions, annotations and line work are designed to be used in tandem with Blender's existing modelling and rendering tool set. While the drawings that MeasureIt-ARCH produces are fundamentally conventional, as are the majority of the techniques that MeasureIt-ARCH employs to create them, MeasureIt-ARCH does provide two simple and relatively novel methods in its drawing systems. MeasureIt-ARCH provides a new method for the placement of dimension elements in 3D space that draws on the dimension's three dimensional context and surrounding geometry order to determine a placement that optimizes legibility. This dimension placement method does not depend on a 2D work plane, a convention that is common in industry standard Computer Aided Design software. MeasureIt-ARCH also implements a new approach for drawing silhouette lines that operates by transforming the silhouetted models geometry in 4D 'Clip Space'. The hope of this work is that MeasureIt-ARCH might be a small step towards creating an Open Source design pipeline for Architects. A step towards creating architectural drawings that can be shared, read, and modified by anyone, within a platform that is itself free to be changed and improved. The creation of MeasureIt-ARCH is motivated by two goals. First, the work aims to create a basic functioning Open Source platform for the creation of architectural drawings within Blender that is publicly and freely available for use. Second, MeasureIt-ARCH's development served as an opportunity to engage in an interdisciplinary act of craft, providing the author an opportunity to explore the act of digital tool making and gain a basic competency in this intersection between Architecture and Computer Science. To achieve these goals, MeasureIt-ARCH's development draws on references from the history of line drawing and dimensioning within Architecture and Computer Science. On the Architectural side, we make use of the history of architectural drawing and dimensioning conventions as described by Mario Carpo, Alberto Pérez Gómez and others, as well as more contemporary frameworks for the classification of architectural software, such as Mark Bew and Mervyn Richard's BIM Levels framework, in order to help determine the scope of MeasureIt-ARCH's feature set. When crafting MeasureIt-ARCH, precedent works from the field of Computer Science that implement methods for producing line drawings from 3D models helped inform the author’s approach to line drawing. In particular this work draws on the overview of line drawing methods produced by Bénard Pierre and Aaron Hertzmann, Arthur Appel's method for line drawing using 'Quantitative Invisibility', the techniques employed in the Freestyle line drawing system created by Grabli et al. as well as other to help inform MeasureIt-ARCH's simple drawing tools. Beyond discussing MeasureIt-ARCH's development and its motivations, this thesis also provides three small speculative discussions about the implications that an Open Source design tool might have on the architectural profession. We investigate MeasureIt-ARCH's use for small scale architectural projects in a practical setting, using it's tool set to produce conceptual design and renovation drawings for cottages at the Lodge at Pine Cove. We provide a demonstration of how MeasureIt-ARCH and Blender can integrate with external systems and other Blender add-ons to produce a proof of concept, dynamic data visualization of the Noosphere installation at the Futurium center in Berlin by the Living Architecture Systems Group. Finally, we discuss the tool's potential to facilitate greater engagement with the Open Source Architecture (OSArc) movement by illustrating a case study of the work done by Alastair Parvin and Clayton Prest on the WikiHouse project, and by highlighting the challenges that face OSArc projects as they try to produce Open Source Architecture without an Open Source design software

Digital photogrammetry for visualisation in architecture and archaeology

Bibliography: leaves 117-125.The task of recording our physical heritage is of significant importance: our past cannot be divorced from the present and it plays an integral part in the shaping of our future. This applies not only to structures that are hundreds of years old, but relatively more recent architectural structures also require adequate documentation if they are to be preserved for future generations. In recording such structures, the traditional 2D methods are proving inadequate. It will be beneficial to conservationists, archaeologists, researchers, historians and students alike if accurate and extensive digital 3D models of archaeological structures can be generated. This thesis investigates a method of creating such models, using digital photogrammetry. Three different types of model were generated: 1. the simple CAD (Computer Aided Design) model; 2. an amalgamation of 3D line drawings; and 3. an accurate surface model of the building using DSMs (Digital Surface Models) and orthophotos

A framework for digital sunken relief generation based on 3D geometric models

Sunken relief is a special art form of sculpture whereby the depicted shapes are sunk into a given surface. This is traditionally created by laboriously carving materials such as stone. Sunken reliefs often utilize the engraved lines or strokes to strengthen the impressions of a 3D presence and to highlight the features which otherwise are unrevealed. In other types of reliefs, smooth surfaces and their shadows convey such information in a coherent manner. Existing methods for relief generation are focused on forming a smooth surface with a shallow depth which provides the presence of 3D figures. Such methods unfortunately do not help the art form of sunken reliefs as they omit the presence of feature lines. We propose a framework to produce sunken reliefs from a known 3D geometry, which transforms the 3D objects into three layers of input to incorporate the contour lines seamlessly with the smooth surfaces. The three input layers take the advantages of the geometric information and the visual cues to assist the relief generation. This framework alters existing techniques in line drawings and relief generation, and then combines them organically for this particular purpose

3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks

We propose a method for reconstructing 3D shapes from 2D sketches in the form of line drawings. Our method takes as input a single sketch, or multiple sketches, and outputs a dense point cloud representing a 3D reconstruction of the input sketch(es). The point cloud is then converted into a polygon mesh. At the heart of our method lies a deep, encoder-decoder network. The encoder converts the sketch into a compact representation encoding shape information. The decoder converts this representation into depth and normal maps capturing the underlying surface from several output viewpoints. The multi-view maps are then consolidated into a 3D point cloud by solving an optimization problem that fuses depth and normals across all viewpoints. Based on our experiments, compared to other methods, such as volumetric networks, our architecture offers several advantages, including more faithful reconstruction, higher output surface resolution, better preservation of topology and shape structure.Comment: 3DV 2017 (oral

Algorithmic Perception of Vertices in Sketched Drawings of Polyhedral Shapes

In this article, visual perception principles were used to build an artificial perception model aimed at developing an algorithm for detecting junctions in line drawings of polyhedral objects that are vectorized from hand-drawn sketches. The detection is performed in two dimensions (2D), before any 3D model is available and minimal information about the shape depicted by the sketch is used. The goal of this approach is to not only detect junctions in careful sketches created by skilled engineers and designers but also detect junctions when skilled people draw casually to quickly convey rough ideas. Current approaches for extracting junctions from digital images are mostly incomplete, as they simply merge endpoints that are near each other, thus ignoring the fact that different vertices may be represented by different (but close) junctions and that the endpoints of lines that depict edges that share a common vertex may not necessarily be close to each other, particularly in quickly sketched drawings. We describe and validate a new algorithm that uses these perceptual findings to merge tips of line segments into 2D junctions that are assumed to depict 3D vertices