Research Report FWF S9206 Helmut Pottmann Geometric Modeling & Industrial Geometry.

Slides:



Advertisements
Similar presentations
Coherent Laplacian 3D protrusion segmentation Oxford Brookes Vision Group Queen Mary, University of London, 11/12/2009 Fabio Cuzzolin.
Advertisements

Multi-view Stereo via Volumetric Graph-cuts
Image Registration  Mapping of Evolution. Registration Goals Assume the correspondences are known Find such f() and g() such that the images are best.
1 st Meeting, Industrial Geometry, 2005 Approximating Solids by Balls (in collaboration with subproject: "Applications of Higher Geometrics") Bernhard.
GRAPP, Lisbon, February 2009 University of Ioannina Skeleton-based Rigid Skinning for Character Animation Andreas Vasilakis and Ioannis Fudos Department.
Developable Surface Fitting to Point Clouds Martin Peternell Computer Aided Geometric Design 21(2004) Reporter: Xingwang Zhang June 19, 2005.
Differential geometry I
Active Contours, Level Sets, and Image Segmentation
Input Space versus Feature Space in Kernel- Based Methods Scholkopf, Mika, Burges, Knirsch, Muller, Ratsch, Smola presented by: Joe Drish Department of.
5/13/2015CAM Talk G.Kamberova Computer Vision Introduction Gerda Kamberova Department of Computer Science Hofstra University.
Robust Global Registration Natasha Gelfand Niloy Mitra Leonidas Guibas Helmut Pottmann.
Automatic Feature Extraction for Multi-view 3D Face Recognition
Discrete Geometry Tutorial 2 1
Shape Space Exploration of Constrained Meshes Yongliang Yang, Yijun Yang, Helmut Pottmann, Niloy J. Mitra.
Instructor: Mircea Nicolescu Lecture 13 CS 485 / 685 Computer Vision.
Human Body Shape Estimation from Single Image Moin Nabi Computer Vision Lab. ©IPM - Dec
A new approach for modeling and rendering existing architectural scenes from a sparse set of still photographs Combines both geometry-based and image.
GATE D Object Representations (GATE-540) Dr.Çağatay ÜNDEĞER Instructor Middle East Technical University, GameTechnologies & General Manager SimBT.
Offset of curves. Alina Shaikhet (CS, Technion)
1 GEOMETRIE Geometrie in der Technik H. Pottmann TU Wien SS 2007.
IMA Tutorial, Instantaneous Motions - Applications to Problems in Reverse Engineering and 3D Inspection H. Pottmann.
Niloy J. Mitra1, Natasha Gelfand1, Helmut Pottmann2, Leonidas J
Non-Euclidean Embedding
1Ellen L. Walker Matching Find a smaller image in a larger image Applications Find object / pattern of interest in a larger picture Identify moving objects.
A Global Geometric Framework for Nonlinear Dimensionality Reduction Joshua B. Tenenbaum, Vin de Silva, John C. Langford Presented by Napat Triroj.
The Terrapins Computer Vision Laboratory University of Maryland.
Image Primitives and Correspondence
Robust Statistical Estimation of Curvature on Discretized Surfaces Evangelos Kalogerakis Patricio Simari Derek Nowrouzezahrai Karan Singh Symposium on.
00/4/103DVIP-011 Part Three: Descriptions of 3-D Objects and Scenes.
Nonlinear Dimensionality Reduction Approaches. Dimensionality Reduction The goal: The meaningful low-dimensional structures hidden in their high-dimensional.
Modeling and representation 1 – comparative review and polygon mesh models 2.1 Introduction 2.2 Polygonal representation of three-dimensional objects 2.3.
Manifold learning: Locally Linear Embedding Jieping Ye Department of Computer Science and Engineering Arizona State University
Dual Evolution for Geometric Reconstruction Huaiping Yang (FSP Project S09202) Johannes Kepler University of Linz 1 st FSP-Meeting in Graz, Nov ,
Intrinsic Parameterization for Surface Meshes Mathieu Desbrun, Mark Meyer, Pierre Alliez CS598MJG Presented by Wei-Wen Feng 2004/10/5.
Orthogonal moments Motivation for using OG moments Stable calculation by recurrent relations Easier and stable image reconstruction - set of orthogonal.
11/19/02 (c) 2002, University of Wisconsin, CS 559 Last Time Many, many modeling techniques –Polygon meshes –Parametric instancing –Hierarchical modeling.
Gwangju Institute of Science and Technology Intelligent Design and Graphics Laboratory Multi-scale tensor voting for feature extraction from unstructured.
Rational surfaces with linear normals and their convolutions with rational surfaces Maria Lucia Sampoli, Martin Peternell, Bert J ü ttler Computer Aided.
V. Space Curves Types of curves Explicit Implicit Parametric.
Course 13 Curves and Surfaces. Course 13 Curves and Surface Surface Representation Representation Interpolation Approximation Surface Segmentation.
Medical Image Analysis Image Registration Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
PCB Soldering Inspection. Structured Highlight approach Structured Highlight method is applied to illuminating and imaging specular surfaces which yields.
Computer Animation Rick Parent Computer Animation Algorithms and Techniques Optimization & Constraints Add mention of global techiques Add mention of calculus.
Normal Curvature of Surface p  N T Local geometry at a surface point p:  surface normal N. The plane containing N and T cuts out a curve  on the surface.
Extracting features from spatio-temporal volumes (STVs) for activity recognition Dheeraj Singaraju Reading group: 06/29/06.
Raquel A. Romano 1 Scientific Computing Seminar May 12, 2004 Projective Geometry for Computer Vision Projective Geometry for Computer Vision Raquel A.
Geometry of Shape Manifolds
CS654: Digital Image Analysis Lecture 36: Feature Extraction and Analysis.
3D Face Recognition Using Range Images
CS 376 Introduction to Computer Graphics 04 / 25 / 2007 Instructor: Michael Eckmann.
Controlled-Distortion Constrained Global Parametrization
Geometric Modeling with Conical Meshes and Developable Surfaces SIGGRAPH 2006 Yang Liu, Helmut Pottmann, Johannes Wallner, Yong-Liang Yang and Wenping.
CS654: Digital Image Analysis
A D V A N C E D C O M P U T E R G R A P H I C S CMSC 635 January 15, 2013 Quadric Error Metrics 1/20 Geometric Morphometrics Feb 27, 2013 Geometric Morphologyd.
CS559: Computer Graphics Final Review Li Zhang Spring 2010.
Energy-minimizing Curve Design Gang Xu Zhejiang University Ouyang Building, 20-December-2006.
Mesh Resampling Wolfgang Knoll, Reinhard Russ, Cornelia Hasil 1 Institute of Computer Graphics and Algorithms Vienna University of Technology.
Image features and properties. Image content representation The simplest representation of an image pattern is to list image pixels, one after the other.
J. Flusser, T. Suk, and B. Zitová Moments and Moment Invariants in Pattern Recognition The slides accompanying.
Image Features (I) Dr. Chang Shu COMP 4900C Winter 2008.
SIAM Conference on Geometric Desing & Computing Approximation of spatial data with shape constraints Maria Lucia Sampoli University of Siena, Italy.
Introduction to Parametric Curve and Surface Modeling.
Intrinsic Data Geometry from a Training Set
Range Image Segmentation for Modeling and Object Detection in Urban Scenes Cecilia Chen & Ioannis Stamos Computer Science Department Graduate Center, Hunter.
Motion and Optical Flow
RGB-D Image for Scene Recognition by Jiaqi Guo
Descriptions of 3-D Objects and Scenes
Introduction to Parametric Curve and Surface Modeling
Single View Modeling of Free-Form Scenes
CS654: Digital Image Analysis
Presentation transcript:

Research Report FWF S9206 Helmut Pottmann Geometric Modeling & Industrial Geometry

2 Map labeling algorithm Collision free initial position using digitized images Iterative improvement using force directed optimization

3 Surface fitting in feature sensitive metric

4 Integral invariants Integration over local neighborhoods „Curvature“ on various scales

5 Minkowski sum boundary surfaces of 3D objects Minkowski sum A+B of objects A and B is the outer envelope of B with respect to all translations determined by points a  A.

6 Parametrization of rational and convolution surfaces The convolution surface A*B is the generalized offset of A w.r.t. B. Thm.: The convolution of any rational surface and a polynomial surface with a linear normal vector field is always rational.

7 Line element geometry Line element = line + point on it Surface recognition, reconstruction; segmentation

8 Geometric automatic extraction of sulcal fundi Fundi = deepest regions of cortex; use a geodesic depth measure w.r.t. to hull surface computed with level set method

9 3D shape morphing based on geodesics in shape spaces

10 Scientific talks H. Pottmann: Univ. Innsbruck, Tsinghua Univ., Seoul Nat. Univ.: Integral invariants M. Peternell, SIAM’05: Envelopes of moving solids M. Peternell, SIAM’05: Constrained Surface Approximation from a Geometric Optimization Perspective M. Hofer, SIAM’05: 3D Shape Recognition and Reconstruction Based on Line Element Geometry