KES2009 Reflectance Analysis

De Grupo de Inteligencia Computacional (GIC)
Special Session on Reflectance Analysis
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Chairs

Computational Intelligence Group, UPV/EHU

Contact email

[1]

Rationale for the special session

Reflectance Analysis is a key process in computer vision systems and applications. It allows the robust segmentation of the images. It has been studied and applied in autononomous robotics, multimodal human computer interaction and remote sensing. There are some physical models of the interaction between light and the surfaces that have been used either for image rendering (visualization) or for image analysis. The most general is the BRDF model used in visualization programs. The Dichromatic Reflection Model has been proposed for the reflectance analysis of general images. This model is local and generalizations involving spatial information and non-linear effects will greatly increase its usefulness in real life applications. Knowledge Engineering and Computational Inteligence tools may provide this generalization. Other related paradigms that can benefit from the application of Computational Intelligence are Color Constancy and Retinex. The special session is intended to gather researchers applying Reflectance Analysis to real life problems and applications, or proposing innovative computational methods.

Topics of interest

  • Shape from shading
  • Shape from Reflection Analysis
  • Isolating Specular Component
  • Reflectance Maps
  • Reflectance Models
  • Specular and Lambertian Surfaces
  • Geometrics and Photometrics Invariants
  • Methods for Chromatic Illummination Estimation
  • Color Spaces for Reflectance Analysis
  • Mathematical Morphology of Color Spaces and their applicantion in Reflectance Analysis
  • Color Constancy
  • Shadows
  • Computational Intellligence for Reflectance Analysis

Important dates

  • Submission of papers: 1 March 2009
  • Notification of acceptance: 1 April 2009
  • Final paper to be received by: 1 May 2009

Program committee (tentative)

Bruce A. Maxwell
Richard M. Friedhoff
Casey A. Smith
H. Ragheb
R. Hancock
Stephen Grossberg
Z.G. Pan
Jiuai Sun --
J.H. Xin
P. Kakumanu
N. Bourbakis
Hui-Liang Shen
Thomas M. Lehmann --
Todd Zickler
Yihong Wu
Kuk-Jin Yoon
Yoo Jin Choi
In-So Kweon
Javier Toro --
Sei-Wang Chen --
Ron O. Dror
Edward H. Adelson
Alan S. Willsky
Katsushi Ikeuchi
Robby T. Tan
Ko Nishino
Imari Sato
Yana Mileva
Andrés Bruhn
Joachim Weickert
Lavanya Sharan
A. Smolarz
Peter Orbanz
Lin Li
Gus Wiseman
Jun’ichiro Seyama
J. Lellmann
J. Balzer --
A. Rieder
J. Beyerer
Rogerio Feris
Ramesh Raskar
Karhan Tan
Matthew Turk
Roger Trias-Sanz
Georges Stamon
Jean Louchet
Guy Godin
Todd Zickler
Marc Ebner
Harold B. Westlund
Gary W. Meyer
Tandent Vision Science, Inc. USA
Tandent Vision Science, Inc. USA
Tandent Vision Science, Inc. USA
Digital Imaging Research Centre, Kingston University London
Department of Computer Science, University of York
Laboratory of Sensorimotor Research, USA
State Key Lab of CAD&CG, Zhejiang University, China
Machine Vision Lab, Faculty of CEMS, University of the West of England, UK
The Hong Kong Polytechnic University, Hong Kong, China
ITRI/Department of Computer Science and Engineering, Wright State University, USA
ITRI/Department of Computer Science and Engineering, Wright State University, USA
Department of Information and Electronic Engineering, Zhejiang University, China
Institute of Medical Informatics, Aachen University of Technology, Germany
Harvard University, Cambridge, USA
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Robotics and Computer Vision Lab. Dept. of EECS, KAIST, Korea
Mobile Multimedia Lab. LG Electronics Institute of Technology
Robotics and Computer Vision Lab. Dept. of EECS, KAIST, Korea
Grupo de Ingeniería Biomédica, Universidad de los Andes, Venezuela
Department of Computer Science and Information Engineering National Taiwan Normal University, Taiwan
Department of Electrical Engineering and Computer Science, MIT
Department of Brain and Cognitive Sciences, MIT
Department of Electrical Engineering and Computer Science, MIT
Department of Computer Science The University of Tokyo
Department of Computer Science The University of Tokyo
Department of Computer Science Columbia University
The University of Tokyo
Mathematical Image Analysis Group, Saarland University, Germany
Mathematical Image Analysis Group, Saarland University, Germany
Mathematical Image Analysis Group, Saarland University, Germany
Department of Electrical Engineering and Computer Science, MIT
University of Technology of Troyes, ICD Laboratory FRE CNRS, FRANCE
Institute of Computational Science, ETH Zürich
Department of Earth Sciences, Indiana University – Purdue University, USA
Department of Mathematics, University of California
Department of Psychology, Tokyo, Japan
Informatik (ITEC), Department of Computer Science, University of Karlsruhe, Germany
Geometric Modeling and Industrial Geometry, Institute of Discrete Mathematics and Geometry, Vienna University of Technology
Informatik (ITEC), Department of Computer Science, University of Karlsruhe, Germany
Department of Mathematics, University of Karlsruhe, Karlsruhe, Germany
UCSB–University of California, Santa Barbara, USA
MERL–Mitsubishi Electric Research Labs, Cambridge, USA
MERL–Mitsubishi Electric Research Labs, Cambridge, USA
UCSB–University of California, Santa Barbara, USA
Institut Géographique National, France
Université de Paris, France
Equipe COMPLEX, INRIA, France
Equipe COMPLEX, INRIA, France
Harvard University, USA
Universität Würzburg, Germany
Departament of computer and Information Science, Canada
Departament of computer and Information Science, U.S.A




Paper submission

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Conference proceedings will be published by Springer-Verlag

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