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Skeleton Extraction of 3D Objects by Radial Basis Functions for Content-based Retrieval in MPEG-7

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. Previous Collaboration: MPEG-4 Based.

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Skeleton Extraction of 3D Objects by Radial Basis Functions for Content-based Retrieval in MPEG-7

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

  5. 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

  6. 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.

  7. 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

  8. 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

  9. 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 µ

  10. 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

  11. 445 3D obejcts http://3dsite.dhs.org/~dynamic 3D Object Retrieval Target model Similarity Search results

  12. 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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