Skeleton Extraction of 3D Objects by Radial Basis Functions for Contentbased Retrieval in MPEG7 - PowerPoint PPT Presentation

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Skeleton Extraction of 3D Objects by Radial Basis Functions for Contentbased Retrieval in MPEG7

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Title: Skeleton Extraction of 3D Objects by Radial Basis Functions for Contentbased Retrieval in MPEG7


1
Skeleton Extraction of 3D Objects by Radial Basis
Functions for Content-based Retrieval in MPEG-7
  • Ming Ouhyoung
  • Fu-Che Wu, Wan-Chun Ma,
  • Communication and Multimedia Lab
  • Dept. of Computer Science and Information
    Engineering,
  • National Taiwan University

2
Previous Collaboration MPEG-4 Based
  • French Driven Talking Head and Lip Motion
    Analysis
  • Realistic 3D Facial Animation Parameters from
    Mirror-Reflected Multi-view Video
  • MPEG-4 Based
  • Demo of the above ( ananova,anim2, track)

3
MPEG-4 to MPEG-7 Transition
  • A New 3 Year Collaborative Project in Multimedia
    Lab, National Taiwan University
  • Skeleton Extraction of 3D Objects for
    Content-based Retrieval in MPEG-7

4
(No Transcript)
5
3D Object Retrieval
Target model
Similarity
Search results
  • 445 3D obejcts
  • http//3dsite.dhs.org/dynamic

6
Part 1 3D Object Retrieval
  • For each vertex of the object, calculate a sum of
    the geodesic distance from this vertex to others
  • Get a Reeb graph, where each node represents a
    region according to the value
  • The similarity of two objects is calculated using
    area and length of the node of their Reeb graph

7
Previous Work
  • Masaki Hilaga, Yoshihisa Shinagawa, Taku Kohmura
    and Tosiyasu L. Kunii, Topology Matching for
    Fully Automatic Similarity Estimation of 3D
    Shapes, Proceedings of ACM SIGGRAPH, 2001.
  • Robert Osada, Thomas Funkhouser, Bernard Chazelle
    and David Dobkin Matching 3D Models with Shape
    Distributions, Proceedings of Workshop on
    Shape-Based Retrieval and Analysis of 3D Models,
    Princeton, USA, Oct. 2001.

8
Previous Work
  • Christopher M. Cyr and Benjamin B. Kimia, 3D
    Object Recognition Using Shape Similiarity-Based
    Aspect Graph, 2001.
  • Michael Elad, Ayellet Tal and Sigal Ar, Content
    Based Retrieval of VRML Objects A Iterative and
    Interactive Approach, 2001

9
Using a skeletal structure of a 3D shape as a
search key
  • Reeb graph
  • Always consists of a one-dimensional graph
    structure
  • Invariant to translation, rotation and scaling
  • Robust against connectivity changes caused by
    simplification, subdivision and remesh
  • Resistant against noise and certain changes due
    to deformation
  • Introduce a multiresolutional structure

10
Geodesic distance
  • The distance from point to point on a surface
    (the length of shortest path)
  • Lazarus et al. proposed a level set diagram (LSD)
    structure in which geodesic distance from a
    source point is used as the function ยต

11
3D Object Retrieval
  • The approach represents the skeletal and
    topological structure of a 3D object
  • Search 3D object automatically and quickly
  • Robust against translation, rotation, scaling,
    simplification, subdivision, noise, deformation
  • Demo
  • http//3dsite.dhs.org/dynamic
  • 445 objects in the database
  • 0.08 sec for comparing two objects on the average

12
3D Object Retrieval
Target model
Similarity
Search results
  • 445 3D obejcts
  • http//3dsite.dhs.org/dynamic

13
(No Transcript)
14
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15
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16
Skeletal Representation by Radial Basis Function
  • Improvements over Multi-resolution Reeb Graph
    not exactly a skeleton of mesh models
  • How about Medial Axis Transformation
    Representation?
  • Skip to part 2 slides
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