3D Object Recognition and 2-Simplex Meshes

Slides:



Advertisements
Similar presentations
3D shapes.
Advertisements

Extended Gaussian Images
Chapter 8 Content-Based Image Retrieval. Query By Keyword: Some textual attributes (keywords) should be maintained for each image. The image can be indexed.
Discrete Geometry Tutorial 2 1
MATHIEU GAUTHIER PIERRE POULIN LIGUM, DEPT. I.R.O. UNIVERSITÉ DE MONTRÉAL GRAPHICS INTERFACE 2009 Preserving Sharp Edges in Geometry Images.
1 Minimum Ratio Contours For Meshes Andrew Clements Hao Zhang gruvi graphics + usability + visualization.
Tessellation Simulation Project
USING GEOMETRIC MODELING FOR FEATURE RECOGNITION IN ARCHAEOLOGICAL VESSELS DEZHI LIU FEATURE GROUP PRISM/ASU 3DK – 3DK – September 15, 2000.
1 Numerical geometry of non-rigid shapes Lecture II – Numerical Tools Numerical geometry of shapes Lecture II – Numerical Tools non-rigid Alex Bronstein.
Chapter 3 2D AND 3D SPATIAL DATA REPRESENTATIONS 김 정 준.
Summer Work: 3d Viewer Medial Axis Viewer Mesh Editor Alexander K. Bowman 30 August 2004.
CS CS 175 – Week 4 Triangle Mesh Smoothing Discrete Differential Geometry.
A Brief Survey on Face Recognition Systems Amir Omidvarnia March 2007.
Ten Minute Math. Face Part of a shape that is flat.(Or curved) E.g. A cube has 6 of these.
3D Models and Matching representations for 3D object models
Created by Mandy Plunkett Modified by Charlotte Stripling
AdvisorStudent Dr. Jia Li Shaojun Liu Dept. of Computer Science and Engineering, Oakland University 3D Shape Classification Using Conformal Mapping In.
Tracking Surfaces with Evolving Topology Morten Bojsen-Hansen IST Austria Hao Li Columbia University Chris Wojtan IST Austria.
HW: Complete WB 112 and finish Mtn. Math- Week 18 Do #1-8 (the entire page of WB 112) Make sure and follow the directions: 1- Name each solid figure 2-
3-Dimensional Figures. Polygons (Two dimensional) A polygon is a geometric figure that is made up of three or more line segments that intersect only at.
Surface Simplification Using Quadric Error Metrics Michael Garland Paul S. Heckbert.
Geometric Perspectives. Everything has a name… Face Corner (Vertex) Edges.
3D Objects Subject:T0934 / Multimedia Programming Foundation Session:12 Tahun:2009 Versi:1/0.
Geometry Images Xiang Gu Harvard University Steven J. Gortler Harvard university Hugues Hoppe Microsoft Research Some slides taken from Hugues Hoppe.
Topic 11 Lesson 1 = Flat Surfaces, Vertices, and Edges Lesson 2 = Relating Plane Shapes to Solid Figures Lesson 3 = Making New Shapes Lesson 4 = Cutting.
Mesh Data Structure. Meshes Boundary edge: adjacent to 1 face Regular edge: adjacent to 2 faces Singular edge: adjacent to >2 faces Mesh: straight-line.
(7.6) Geometry and spatial reasoning The student compares and classifies shapes and solids using geometric vocabulary and properties. The student is expected.
Identify the Faces, Edges, Vertices.
3D SHAPES By Keith & Callum. cube the cube has 6 faces It has 8 vertices It has 12 edges.
Geometric Hashing: A General and Efficient Model-Based Recognition Scheme Yehezkel Lamdan and Haim J. Wolfson ICCV 1988 Presented by Budi Purnomo Nov 23rd.
What are these shapes? squarecircletrianglerectangle How many sides do each have? How many points do each have?
Space Figures & Cross-Sections
Automatic License Plate Location Using Template Matching University of Wisconsin - Madison ECE 533 Image Processing Fall 2004 Project Kerry Widder.
Content-Based Image Retrieval QBIC Homepage The State Hermitage Museum db2www/qbicSearch.mac/qbic?selLang=English.
Three Dimensional Figures
What is a 3-D Shape? This is a cube height depth length It has 3 dimensions – length, height and depth. All 3-D shapes are solids.
2 pt 3 pt 4 pt 5pt 1 pt 2 pt 3 pt 4 pt 5 pt 1 pt 2pt 3 pt 4pt 5 pt 1pt 2pt 3 pt 4 pt 5 pt 1 pt 2 pt 3 pt 4pt 5 pt 1pt Vocab 1 Vocab 2 Transformations CompositionsMiscellaneous.
Matching Geometric Models via Alignment Alignment is the most common paradigm for matching 3D models to either 2D or 3D data. The steps are: 1. hypothesize.
COMPUTER GRAPHICS CS 482 – FALL 2015 SEPTEMBER 10, 2015 TRIANGLE MESHES 3D MESHES MESH OPERATIONS.
CDS 301 Fall, 2008 Domain-Modeling Techniques Chap. 8 November 04, 2008 Jie Zhang Copyright ©
8-7 Transformation Objective: Students recognize, describe, and show transformation.
Face recognition using Histograms of Oriented Gradients
Created by Mandy Plunkett Modified by Charlotte Stripling

Geometric attributes.
3D SHAPES.
Tessellations A tessellation is made by reflecting, rotating or translating a shape. A shape will tessellate if it can be used to completely fill a space.
Transformations.
A geometric shape is the geometric information which remains when location, scale, orientation and reflection are removed from the description of a geometric.
Engineering Geometry Engineering geometry is the basic geometric elements and forms used in engineering design. Engineering and technical graphics are.
Unit 3 – Lesson 6 Solids.
Discrete Math 2 Weighted Graph Search Tree
CS475 3D Game Development Level Of Detail Nodes (LOD)
Mean Shift Segmentation
Object Recognition in the Dynamic Link Architecture
3D Models and Matching particular matching techniques
Introduction to Basic Animation Model Building
3D objects Saturday, 17 November 2018.
Domain-Modeling Techniques
Geometric Hashing: An Overview
RIO: Relational Indexing for Object Recognition
Brief Review of Recognition + Context
Lecture 3 : Isosurface Extraction
Volume Graphics (lecture 4 : Isosurface Extraction)
Geometric Solids All bounded three-dimensional geometric figures. Examples: Sphere, Cylinders, Cubes, Cones, Pyramids, and Prisms.
Geometric Solids All bounded three-dimensional geometric figures. Examples: Sphere, Cylinders, Cubes, Cones, Pyramids, and Prisms.
Question 13.
Rudro Samanta Princeton University
Guess the Shape!.
High-Level Vision Object Recognition II.
Presentation transcript:

3D Object Recognition and 2-Simplex Meshes By Gerald Dalley

Overview Some popular 3D object recognition techniques Appearance-based matching Feature matching Regular mesh tesselation 2-Simplex Meshes Spherical Attribute Images For further reading 1 May 2001 3D Vehicle Recognition

Popular Recognition Techniques: Appearance-Based Matching Basic steps Sample a view-sphere Record feature measurements as observable from a camera at each view-sphere sample point (create templates) Compare observed data with each template from each model Choose the model and orientation that provides the best match Requires sufficiently fine sampling of the view sphere 1 May 2001 3D Vehicle Recognition

Popular Recognition Techniques: Feature Matching Ravi’s work, Rick’s local features Basic steps Find features invariant to rotation and translation Build an attributed graph Nodes: features Arcs: spatial arrangement Choose the model whose graph is most similar 1 May 2001 3D Vehicle Recognition

Popular Recognition Techniques: Regular Mesh Tesselation “Regularly” sample the mesh Square grid Triangularization 2-Simplex Measure feature values at mesh vertices Vertex-by-vertex comparison Image from [3] 1 May 2001 3D Vehicle Recognition

2-Simplex Meshes Dual of triangularization Triangle face  simplex vertex Triangle vertex  simplex face 1 May 2001 3D Vehicle Recognition

2-Simplex Meshes: Two Examples 1 May 2001 3D Vehicle Recognition

2-Simplex Meshes: Topological & Geometric Modifications f1 and f3 merged f4 f2 f1 V1 f2 f4 V2 f3 f1 V1' Edge Swap f4 f2 Edge Removal V2' f3 1 May 2001 3D Vehicle Recognition

2-Simplex Meshes: Edge Removal Example 1 May 2001 3D Vehicle Recognition

Spherical Attribute Images SAI: Point size  vertex curvature 2D Contour 1-Simplex Mesh 1 May 2001 3D Vehicle Recognition

Spherical Attribute Images: 2D SAI Examples 1 May 2001 3D Vehicle Recognition

Spherical Attribute Images: Recognition 1 May 2001 3D Vehicle Recognition

Further Reading 1 May 2001 3D Vehicle Recognition