Shape computations without compositions

Parametric CAD supports design explorations through generative methods which compose and transform geometric elements. This paper argues that elementary shape computations do not always correspond to valid compositional shape structures. In many design cases generative rules correspond to compositional structures, but for relatively simple shapes and rules it is not always possible to assign a corresponding compositional structure of parts which account for all operations of the computation. This problem is brought into strong relief when design processes generate multiple compositions according to purpose, such as product structure, assembly, manufacture, etc. Is it possible to specify shape computations which generate just these compositions of parts or are there additional emergent shapes and features? In parallel, combining two compositions would require the associated combined computations to yield a valid composition. Simple examples are presented which throw light on the issues in integrating different product descriptions (i.e. compositions) within parametric CAD

Modeling 3D animals from a side-view sketch

Shape Modeling International 2014International audienceUsing 2D contour sketches as input is an attractive solution for easing the creation of 3D models. This paper tackles the problem of creating 3D models of animals from a single, side-view sketch. We use the a priori assumptions of smoothness and structural symmetry of the animal about the sagittal plane to inform the 3D reconstruction. Our contributions include methods for identifying and inferring the contours of shape parts from the input sketch, a method for identifying the hierarchy of these structural parts including the detection of approximate symmetric pairs, and a hierarchical algorithm for positioning and blending these parts into a consistent 3D implicit-surface-based model. We validate this pipeline by showing that a number of plausible animal shapes can be automatically constructed from a single sketch

Stereoscopic Sketchpad: 3D Digital Ink

--Context-- This project looked at the development of a stereoscopic 3D environment in which a user is able to draw freely in all three dimensions. The main focus was on the storage and manipulation of the ‘digital ink’ with which the user draws. For a drawing and sketching package to be effective it must not only have an easy to use user interface, it must be able to handle all input data quickly and efficiently so that the user is able to focus fully on their drawing. --Background-- When it comes to sketching in three dimensions the majority of applications currently available rely on vector based drawing methods. This is primarily because the applications are designed to take a users two dimensional input and transform this into a three dimensional model. Having the sketch represented as vectors makes it simpler for the program to act upon its geometry and thus convert it to a model. There are a number of methods to achieve this aim including Gesture Based Modelling, Reconstruction and Blobby Inflation. Other vector based applications focus on the creation of curves allowing the user to draw within or on existing 3D models. They also allow the user to create wire frame type models. These stroke based applications bring the user closer to traditional sketching rather than the more structured modelling methods detailed. While at present the field is inundated with vector based applications mainly focused upon sketch-based modelling there are significantly less voxel based applications. The majority of these applications focus on the deformation and sculpting of voxmaps, almost the opposite of drawing and sketching, and the creation of three dimensional voxmaps from standard two dimensional pixmaps. How to actually sketch freely within a scene represented by a voxmap has rarely been explored. This comes as a surprise when so many of the standard 2D drawing programs in use today are pixel based. --Method-- As part of this project a simple three dimensional drawing program was designed and implemented using C and C++. This tool is known as Sketch3D and was created using a Model View Controller (MVC) architecture. Due to the modular nature of Sketch3Ds system architecture it is possible to plug a range of different data structures into the program to represent the ink in a variety of ways. A series of data structures have been implemented and were tested for efficiency. These structures were a simple list, a 3D array, and an octree. They have been tested for: the time it takes to insert or remove points from the structure; how easy it is to manipulate points once they are stored; and also how the number of points stored effects the draw and rendering times. One of the key issues brought up by this project was devising a means by which a user is able to draw in three dimensions while using only two dimensional input devices. The method settled upon and implemented involves using the mouse or a digital pen to sketch as one would in a standard 2D drawing package but also linking the up and down keyboard keys to the current depth. This allows the user to move in and out of the scene as they draw. A couple of user interface tools were also developed to assist the user. A 3D cursor was implemented and also a toggle, which when on, highlights all of the points intersecting the depth plane on which the cursor currently resides. These tools allow the user to see exactly where they are drawing in relation to previously drawn lines. --Results-- The tests conducted on the data structures clearly revealed that the octree was the most effective data structure. While not the most efficient in every area, it manages to avoid the major pitfalls of the other structures. The list was extremely quick to render and draw to the screen but suffered severely when it comes to finding and manipulating points already stored. In contrast the three dimensional array was able to erase or manipulate points effectively while the draw time rendered the structure effectively useless, taking huge amounts of time to draw each frame. The focus of this research was on how a 3D sketching package would go about storing and accessing the digital ink. This is just a basis for further research in this area and many issues touched upon in this paper will require a more in depth analysis. The primary area of this future research would be the creation of an effective user interface and the introduction of regular sketching package features such as the saving and loading of images

Extracting datums to reconstruct CSG models from 2D engineering sketches of polyhedral shapes

Our goal is to automatically generate CAD 3D models from 2D sketches as part of a design chain where models should be procedural, containing features arranged in a model tree and linked to suitable datums. Current procedural models capture much about the design intent and are easy to edit, but must be created from scratch during the detailed design state—given conceptual sketches as used by designers in the early part of the design process, current sketch-based modeling approaches only output explicit models. Thus, we describe an approach to extract high-level information directly from 2D engineering wireframe sketches and use it to complete a CSG feature tree, which serves as a model tree for a procedural 3D CAD model. Our method extracts procedural model information directly from 2D sketches in the form of a set of features, plus a set of datums and relationships between these features. We detect and analyze features of 2D sketches in isolation, and define the CSG feature tree by the parent–child relationships between features, and combine this information to obtain a complete and consistent CSG feature tree that can be transferred to a 3D modeler, which reconstructs the model. This paper focuses on how to extract the feature datums and the extrusion operation from an input 2D sketch.Funding for open access charge: CRUE-Universitat Jaume

2.5D cartoon models

We present a way to bring cartoon objects and characters into the third dimension, by giving them the ability to rotate and be viewed from any angle. We show how 2D vector art drawings of a cartoon from different views can be used to generate a novel structure, the 2.5D cartoon model, which can be used to simulate 3D rotations and generate plausible renderings of the cartoon from any view. 2.5D cartoon models are easier to create than a full 3D model, and retain the 2D nature of hand-drawn vector art, supporting a wide range of stylizations that need not correspond to any real 3D shape.MathWorks, Inc. (Fellowship

Learning Active Basis Models by EM-Type Algorithms

EM algorithm is a convenient tool for maximum likelihood model fitting when the data are incomplete or when there are latent variables or hidden states. In this review article we explain that EM algorithm is a natural computational scheme for learning image templates of object categories where the learning is not fully supervised. We represent an image template by an active basis model, which is a linear composition of a selected set of localized, elongated and oriented wavelet elements that are allowed to slightly perturb their locations and orientations to account for the deformations of object shapes. The model can be easily learned when the objects in the training images are of the same pose, and appear at the same location and scale. This is often called supervised learning. In the situation where the objects may appear at different unknown locations, orientations and scales in the training images, we have to incorporate the unknown locations, orientations and scales as latent variables into the image generation process, and learn the template by EM-type algorithms. The E-step imputes the unknown locations, orientations and scales based on the currently learned template. This step can be considered self-supervision, which involves using the current template to recognize the objects in the training images. The M-step then relearns the template based on the imputed locations, orientations and scales, and this is essentially the same as supervised learning. So the EM learning process iterates between recognition and supervised learning. We illustrate this scheme by several experiments.Comment: Published in at http://dx.doi.org/10.1214/09-STS281 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Features and design intent in engineering sketches

We investigate the problem of determining design intent from engineering sketches: what did the designer have in mind when sketching a component? Specifically, we consider the unidirectional reverse mapping from form features, as determined from an input sketch, to design features, representing the design intent present in the designer’s mind. We introduce a list of com- mon engineering form features. For each, we list which geometrical cues may be helpful in identifying these features in design sketches, and we list the design features which such form features commonly imply. We show that a reductionist approach which decomposes a diagram into form features can be used to deduce the design intent of the object portrayed in a drawing. We supply experimental results in support of this idea