Plenary Speaker 1

 Multiscale analysis of similarities between images on Riemannian manifolds and applications
Coloma Ballester, Dept de Tecnologies de la Informació i les Comunicacions of the Universitat Pompeu Fabra in Barcelona, Spain

 

 

Abstract :

colomaballester


Image comparison is a main ingredient in many applications in image processing and computer vision such as object recognition, stereo vision, image interpolation, image denoising, exemplar-based image inpainting, among others. The purpose of this talk will be to give an overview of recent techniques allowing to define a multiscale comparison of images defined on Riemannian manifolds and its applications in image and video problems.

The image comparison problem will be formulated as the problem of comparing two patches (local neighborhoods) belonging to each image defined on a Riemannian manifold, which in turn can be defined by the image domain with a suitable metric depending on the image. We will derive from an axiomatic approach a set of multiscale similarity measures that appear as solutions of a degenerate PDE. We will single out some particular instances, in particular, we present a linear model to compare patches defined on two images in R^n endowed with an intrinsic metric which allows to compare them in an affine invariant manner. Besides its genericity, this linear model is selected by its computational feasibility, since it can be approximated leading to an algorithm that has the complexity of the usual patch comparison using a weighted Euclidean distance. We will show applications of this multiscale analysis of similarities to different problems such as interpolation, exemplar-based inpainting and stereo vision.

 

 
Biography :


Coloma Ballester received the degree in Mathematics at the U. Autònoma de Barcelona, the Master "Mathématiques Appliquées à l'Ingénierie" at the U.Paris-IX in 1992 and the Ph.D. in Computer Science at the U. Illes Balears in 1995. After her PhD, she worked at UIB until 1997, and at the CNRS at IHP in Paris, in 1998. Since 1999 Coloma Ballester is an Associate Professor at the Department of Information and Communication Technologies, University Pompeu Fabra, Barcelona.Her research interests include image processing and computer vision. She is currently interested in depth computation, stereo vision and 3D reconstruction, motion estimation, video inpainting and stereo video inpainting, film post-production algorithms, shape recognition, geometric models, and in general in variational models for image processing and computer vision.

Plenary Speaker 2

 Opponent Color Revisited 
Sabine Süsstrunk, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland

 

 

colomaballester

Abstract :


According to the efficient coding hypothesis, the goal of the visual system should be to encode the information presented to the retina with as little redundancy as possible. From a signal processing point of view, the first step in removing redundancy is de-correlation, which removes the second order dependencies in the signal. This principle was explored in the context of trichromatic vision by Buchsbaum and Gottschalk (1) and later Ruderman et al. (2) who found that linear de-correlation of the LMS cone responses matches the opponent color coding in the human visual system.

And yet, there is comparatively little research in image processing and computer vision that explicitly model and incorporate color opponency into solving imaging tasks. A common perception is that “colors” are redundant and/or too correlated to be of any interest, or that they are too complex to deal with.

In this talk I will illustrate with several simple algorithms, such as saliency and super-pixels, that considering opponent colors can significantly improve image processing and computer vision tasks not only in image enhancement but also image segmentation, image ranking, etc. We have additionally extended the concept of “color opponency” to include near-infrared for applications such as scene recognition, object segmentation, and semantic image labeling.

(1) http://rspb.royalsocietypublishing.org/content/220/1218/89.short
(2) http://www.opticsinfobase.org/josaa/abstract.cfm?&uri=josaa-15-8-2036

 

Biography :


Prof. Sabine Süsstrunk leads the Images and Visual Representation Lab (IVRL) in the School of Computer and Communication Sciences (IC) at EPFL since 1999. Her main research areas are in computational photography, color image processing and computer vision, multimedia, and image quality. She has a BS in Scientific Photography from ETH Zürich, Switzerland, a MS in Electronic Publishing from the Rochester Institute of Technology (RIT), Rochester, NY, USA, and a PhD on computing chromatic adaptation from the School of Computing Sciences, University of East Anglia (UEA) in Norwich, UK.   

From 2003-2004, Sabine was a Visiting Scholar in the Computational Color Reproduction Group at Hewlett-Packard Labs in Palo Alto, CA, USA. From 1995-1999, she was the Principle Imaging Researcher at Corbis Corporation in Seattle, WA, USA. From 1991-1995, she was a Visiting Assistant Professor in the School of Photographic Arts and Sciences at the Rochester Institute of Technology (RIT).

Sabine has authored and co-authored over 140 publications, of which 6 have received best paper/demo awards, and holds 8 patents. She served as chair or committee member in many international conferences on color imaging, digital photography, and image systems engineering (General Chair for the IS&T/SPIE Annual Symposium on Electronic Imaging in 2011, Area Chair for IEEE CVPR 2011, Area Chair for IEEE ICIP 2008, 2009, etc.). She was an Associate Editor for the IEEE Transactions on Image Processing from 2007-2011, the Technical Secretary of the International Color Consortium (ICC) from 2000-2001, Vice-President of IS&T, the Society of Imaging Science and Technology, from 1999-2003 and Conference Vice-President from 2011-2014, Director of CIE Division 8 (Commission Internationale de l'Eclairage, Imaging Technology) from 2007-2011, and member of the ACM E.L. Lawler Award Committee for Humanitarian Contributions within Computer Science and Informatics from 2004-2014.

Sabine is a Fellow of IS&T, senior member of IEEE and ACM, and a member of SPIE  and OSA. She is President and member of the board of the EPFL-WISH (Women in Science and Humanities) Foundation. She received the IS&T/SPIE 2013 Electronic Imaging Scientist of the Year Award for her contributions to color imaging, computational photography, and image quality.

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