36-Issue 7

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/2631805

Browse

Browsing 36-Issue 7 by Subject "Computational Geometry and Object Modeling"

Now showing 1 - 5 of 5
  • No Thumbnail Available
    Item
    Data-Driven Sparse Priors of 3D Shapes
    (The Eurographics Association and John Wiley & Sons Ltd., 2016) Remil, Oussama; Xie, Qian; Xie, Xingyu; Xu, Kai; Wang, Jun; Jernej Barbic and Wen-Chieh Lin and Olga Sorkine-Hornung
    We present a sparse optimization framework for extracting sparse shape priors from a collection of 3D models. Shape priors are defined as point-set neighborhoods sampled from shape surfaces which convey important information encompassing normals and local shape characterization. A 3D shape model can be considered to be formed with a set of 3D local shape priors, while most of them are likely to have similar geometry. Our key observation is that the local priors extracted from a family of 3D shapes lie in a very low-dimensional manifold. Consequently, a compact and informative subset of priors can be learned to efficiently encode all shapes of the same family. A comprehensive library of local shape priors is first built with the given collection of 3D models of the same family. We then formulate a global, sparse optimization problem which enforces selecting representative priors while minimizing the reconstruction error. To solve the optimization problem, we design an efficient solver based on the Augmented Lagrangian Multipliers method (ALM). Extensive experiments exhibit the power of our data-driven sparse priors in elegantly solving several high-level shape analysis applications and geometry processing tasks, such as shape retrieval, style analysis and symmetry detection.
  • No Thumbnail Available
    Item
    Modeling, Evaluation and Optimization of Interlocking Shell Pieces
    (The Eurographics Association and John Wiley & Sons Ltd., 2016) Yao, Miaojun; Chen, Zhili; Xu, Weiwei; Wang, Huamin; Jernej Barbic and Wen-Chieh Lin and Olga Sorkine-Hornung
    While the 3D printing technology has become increasingly popular in recent years, it suffers from two critical limitations: expensive printing material and long printing time. An effective solution is to hollow the 3D model into a shell and print the shell by parts. Unfortunately, making shell pieces tightly assembled and easy to disassemble seem to be two contradictory conditions, and there exists no easy way to satisfy them at the same time yet. In this paper, we present a computational system to design an interlocking structure of a partitioned shell model, which uses only male and female connectors to lock shell pieces in the assembled configuration. Given a mesh segmentation input, our system automatically finds an optimal installation plan specifying both the installation order and the installation directions of the pieces, and then builds the models of the shell pieces using optimized shell thickness and connector sizes. To find the optimal installation plan, we develop simulation-based and data-driven metrics, and we incorporate them into an optimal plan search algorithm with fast pruning and local optimization strategies. The whole system is automatic, except for the shape design of the key piece. The interlocking structure does not introduce new gaps on the outer surface, which would become noticeable inevitably due to limited printer precision. Our experiment shows that the assembled object is strong against separation, yet still easy to disassemble.
  • No Thumbnail Available
    Item
    Regression-Based Landmark Detection on Dynamic Human Models
    (The Eurographics Association and John Wiley & Sons Ltd., 2016) Jang, Deok-Kyeong; Lee, Sung-Hee; Jernej Barbic and Wen-Chieh Lin and Olga Sorkine-Hornung
    Detecting anatomical landmarks on various human models with dynamic poses remains an important and challenging problem in computer graphics research. We present a novel framework that consists of two-level regressors for finding correlations between human shapes and landmark positions in both body part and holistic scales. To this end, we first develop pose invariant coordinates of landmarks that represent both local and global shape features by using the pose invariant local shape descriptors and their spatial relationships. Our body part-level regression deals with the shape features from only those body parts that correspond to a certain landmark. In order to do this, we develop a method that identifies such body parts per landmark, by using geometric shape dictionary obtained through the bag of features method. Our method is nearly automatic, as it requires human assistance only once to differentiate the left and right sides. The method also shows the prediction accuracy comparable to or better than those of existing methods, with a test data set containing a large variation of human shapes and poses.
  • No Thumbnail Available
    Item
    Rib-reinforced Shell Structure
    (The Eurographics Association and John Wiley & Sons Ltd., 2016) Li, Wei; Zheng, Anzong; You, Lihua; Yang, Xiaosong; Zhang, Jianjun; Liu, Ligang; Jernej Barbic and Wen-Chieh Lin and Olga Sorkine-Hornung
    Shell structures are extensively used in engineering due to their efficient load-carrying capacity relative to material volume. However, large-span shells require additional supporting structures to strengthen fragile regions. The problem of designing optimal stiffeners is therefore becoming a major challenge for shell applications. To address it, we propose a computational framework to design and optimize rib layout on arbitrary shell to improve the overall structural stiffness and mechanical performance. The essential of our method is to place ribs along the principal stress lines which reflect paths of material continuity and indicates trajectories of internal forces. Given a surface and user-specified external loads, we perform a Finite Element Analysis. Using the resulting principal stress field, we generate a quad-mesh whose edges align with this cross field. Then we extract an initial rib network from the quad-mesh. After simplifying rib network by removing ribs with little contribution, we perform a rib flow optimization which allows ribs to swing on surface to further adjust rib distribution. Finally, we optimize rib cross-section to maximally reduce material usage while achieving certain structural stiffness requirements. We demonstrate that our rib-reinforced shell structures achieve good static performances. And experimental results by 3D printed objects show the effectiveness of our method.
  • No Thumbnail Available
    Item
    Semi-Automatic Conversion of 3D Shape into Flat-Foldable Polygonal Model
    (The Eurographics Association and John Wiley & Sons Ltd., 2016) Miyamoto, Emi; Endo, Yuki; Kanamori, Yoshihiro; Mitani, Jun; Jernej Barbic and Wen-Chieh Lin and Olga Sorkine-Hornung
    This paper presents a method that can convert a given 3D mesh into a flat-foldable model consisting of rigid panels. A previous work proposed a method to assist manual design of a single component of such flat-foldable model, consisting of verticallyconnected side panels as well as horizontal top and bottom panels. Our method semi-automatically generates a more complicated model that approximates the input mesh with multiple convex components. The user specifies the folding direction of each convex component and the fidelity of shape approximation. Given the user inputs, our method optimizes shapes and positions of panels of each convex component in order to make the whole model flat-foldable. The user can check a folding animation of the output model. We demonstrate the e ectiveness of our method by fabricating physical paper prototypes of flat-foldable models.