Tutorials
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The following Professors are offering tutorials at MCPR on June 29, 2013. Professor Raúl Rojas
Tutorial: Hybrid classifiers
Professor Robert Pless
Biography: Robert Pless is a Professor of Computer Science and Engineering at Washington University in St. Louis. His research focus is data driven approach to understanding motion and change in video, with a current focus on long term time-lapse imagery. Dr. Pless has a Bachelors Degree in Computer Science from Cornell University in 1994 and a PhD from the University of Maryland, College Park in 2000. He received the NSF CAREER award in 2006. He has served as chair of the IEEE Workshop on Omnidirectional Vision and Camera Networks (OMNIVIS) in 2003, the MICCAI Workshop on Manifold Learning in Medical Imagery in 2008, and the IEEE Workshop on Motion and Video Computing in 2009.
Tutorial Description: Tutorial: Linear Image Decompositions through Time: More than Dimensionality Reduction
Description: Linear methods such as Principal Component Analysis, Canonical Components Analysis are a cornerstone of image analysis methods. In this tutorial, I will provide an introduction to classical and novel component analysis techniques, with a focus on how can be learned by applying these methods to video or time-lapse data. The first part of the tutorial will review traditional linear techniques such as PCA, LDA, CCA, etc, and will explore extensions that support incremental solutions, often important to apply these methods to large image data sets. When applied to time-varying imagery, these methods create image components and coefficients that have substantial temporal structure. The tutorial will discuss methods of visualizing this structure, and tools that build on this structure to give novel approaches to scene segmentation and understanding motion in video.
Outline: Linear Models
Extensions
Professor Roberto Manduchi
Tutorial:
On Image Noise, or: How To Take a Well Exposed Picture (or a Stack Thereof)
Professor Edgar F. Roman-Rangel
Biography: Edgar Roman-Rangel is a research assistant at the Computer Vision and Multimedia Laboratory of the University of Geneva. His research interests include Computer Vision, Information Retrieval, and Machine Learning, specially applied to real world needs such as cultural heritage, bioinformatics, and social develpment. He obtained his Master degree in Computer Science from the Instituto Tecnológico y de Estudios Superiores de Monterrey (ITESM) in 2006, and his PhD from the École Politechnique Fédérale de Lausanne (EPFL) in 2013.
Tutorial: Review of shape representations
Description: In this tutorial I will introduce several techniques for description of shapes, providing insights about their advantages and drawbacks. The tutorial will continue with the introduction of the projects CODICES and MAAYA that explore shape representations for Maya hieroglyphs, and that have been conducted at the Idiap research institute. Finally, the tutorial will conclude with a short lab that will provide the opportunity to experiment with some of the methods that were presented.
Outline: Review of shape descriptors (1h30’)
A real example (30’)
Optional Hands-on lab (1h)
Professor Sai Ravela
Tutorial: Alignment Models in Vision
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