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Scale Space and Variational Methods in Computer Vision

First International Conference, SSVM 2007, Ischia, Italy, May 30 - June 2, 2007, Proceedings

  • Conference proceedings
  • © 2007

Overview

Editors:
  1. Fiorella Sgallari
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  2. Almerico Murli
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  3. Nikos Paragios
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4485)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: SSVM 2007.

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Table of contents (79 papers)

  1. Oral Presentations

    1. Motion Analysis, Optical Flow, Registration and Tracking

      1. A Variational Approach for Multi-valued Velocity Field Estimation in Transparent Sequences
        • Alonso Ramírez-Manzanares, Mariano Rivera, Pierre Kornprobst, François Lauze
        Pages 227-238
      2. Dense Optical Flow Estimation from the Monogenic Curvature Tensor
        • Di Zang, Lennart Wietzke, Christian Schmaltz, Gerald Sommer
        Pages 239-250
      3. A Consistent Spatio-temporal Motion Estimator for Atmospheric Layers
        • Patrick Héas, Étienne Mémin, Nicolas Papadakis
        Pages 251-263
      4. Paretian Similarity for Partial Comparison of Non-rigid Objects
        • Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel
        Pages 264-275

    2. 3D from Images

      1. Some Remarks on Perspective Shape-from-Shading Models
        • Emiliano Cristiani, Maurizio Falcone, Alessandra Seghini
        Pages 276-287

  2. Poster Presentations

    1. Scale Space and Feature Extraction

      1. Scale-Space Clustering with Recursive Validation
        • Tomoya Sakai, Takuto Komazaki, Atsushi Imiya
        Pages 288-299
      2. Scale Spaces on Lie Groups
        • Remco Duits, Bernhard Burgeth
        Pages 300-312
      3. Convex Inverse Scale Spaces
        • Klaus Frick, Otmar Scherzer
        Pages 313-325
      4. Spatio-temporal Scale-Spaces
        • Daniel Fagerström
        Pages 326-337
      5. A Scale-Space Reeb-Graph of Topological Invariants of Images and Its Applications to Content Identification
        • Jinhui Chao, Shintaro Suzuki
        Pages 338-349
      6. Salient Regions from Scale-Space Trees
        • Jose Roberto Perez Torres, Yuxuan Lan, Richard Harvey
        Pages 350-361
      7. Generic Maximum Likely Scale Selection
        • Kim Steenstrup Pedersen, Marco Loog, Bo Markussen
        Pages 362-373
      8. Combining Different Types of Scale Space Interest Points Using Canonical Sets
        • Frans Kanters, Trip Denton, Ali Shokoufandeh, Luc Florack, Bart ter Haar Romeny
        Pages 374-385
      9. Feature Vector Similarity Based on Local Structure
        • Evgeniya Balmachnova, Luc Florack, Bart ter Haar Romeny
        Pages 386-393
      10. Maximum Likelihood Metameres for Local 2<sup><i>nd</i></sup> Order Image Structure of Natural Images
        • Martin Lillholm, Lewis D Griffin
        Pages 394-405
      11. Fast and Accurate Gaussian Derivatives Based on B-Splines
        • Henri Bouma, Anna Vilanova, Javier Oliván Bescós, Bart M. ter Haar Romeny, Frans A. Gerritsen
        Pages 406-417

    2. Image Enhancement, Reconstruction and Texture Synthesis

      1. Uniform and Textured Regions Separation in Natural Images Towards MPM Adaptive Denoising
        • Noura Azzabou, Nikos Paragios, Frédéric Guichard
        Pages 418-429
      2. The Variational Origin of Motion by Gaussian Curvature
        • Niels Chr. Overgaard, Jan Erik Solem
        Pages 430-441
      3. A Variational Method with a Noise Detector for Impulse Noise Removal
        • Shoushui Chen, Xin Yang
        Pages 442-450
      4. Detection and Completion of Filaments: A Vector Field and PDE Approach
        • Alexis Baudour, Gilles Aubert, Laure Blanc-Féraud
        Pages 451-460
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