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© 2013

Machine Learning for Computer Vision

  • Roberto Cipolla
  • Sebastiano Battiato
  • Giovanni Maria Farinella
Book

Part of the Studies in Computational Intelligence book series (SCI, volume 411)

Table of contents

  1. Front Matter
    Pages 1-18
  2. Cheston Tan, Joel Z. Leibo, Tomaso Poggio
    Pages 1-15
  3. Stefano Soatto
    Pages 17-48
  4. Kristen Grauman, Rob Fergus
    Pages 49-87
  5. Jeroen C. Chua, Inmar E. Givoni, Ryan P. Adams, Brendan J. Frey
    Pages 89-117
  6. Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore et al.
    Pages 119-135
  7. Minh-Tri Pham, Oliver J. Woodford, Frank Perbet, Atsuto Maki, Riccardo Gherardi, Björn Stenger et al.
    Pages 137-162
  8. Tae-Kyun Kim, Roberto Cipolla
    Pages 163-196
  9. Murtaza Taj, Andrea Cavallaro
    Pages 197-214
  10. Alberto Broggi, Stefano Cattani, Paolo Medici, Paolo Zani
    Pages 215-250

About this book

Introduction

Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout. The International Computer Vision Summer School - ICVSS was established in 2007 to provide both an objective and clear overview and an in-depth analysis of the state-of-the-art research in Computer Vision. The courses are delivered by world renowned experts in the field, from both academia and industry, and cover both theoretical and practical aspects of real Computer Vision problems. The school is organized every year by University of Cambridge (Computer Vision and Robotics Group) and University of Catania (Image Processing Lab). Different topics are covered each year. A summary of the past Computer Vision Summer Schools can be found at: http://www.dmi.unict.it/icvss This edited volume contains a selection of articles covering some of the talks and tutorials held during the last editions of the school. The chapters provide an in-depth overview of challenging areas with key references to the existing literature.

Keywords

Computational Intelligence Computer Vision Image Analyis Machine Learning Video Analysis

Editors and affiliations

  • Roberto Cipolla
    • 1
  • Sebastiano Battiato
    • 2
  • Giovanni Maria Farinella
    • 3
  1. 1.Department of EngineeringUniversity of CambridgeCambridgeUnited Kingdom
  2. 2.Dipartimento di Matematica e InformaticaUniversità di CataniaCataniaItaly
  3. 3.Dipartimento di Matematica e InformaticaUniversità di CataniaCataniaItaly

Bibliographic information

  • Book Title Machine Learning for Computer Vision
  • Editors Roberto Cipolla
    Sebastiano Battiato
    Giovanni Maria Farinella
  • Series Title Studies in Computational Intelligence
  • DOI https://doi.org/10.1007/978-3-642-28661-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-642-28660-5
  • Softcover ISBN 978-3-642-44686-3
  • eBook ISBN 978-3-642-28661-2
  • Series ISSN 1860-949X
  • Series E-ISSN 1860-9503
  • Edition Number 1
  • Number of Pages XXII, 250
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Computational Intelligence
    Artificial Intelligence
    Image Processing and Computer Vision
  • Buy this book on publisher's site

Reviews

From the reviews:

“This book should … be of interest to anybody involved in computer vision or image and video analysis, as it presents many challenging scenarios to the machine learning community. … this book presents a snapshot of key research in the areas of computer vision and machine learning. On this level, the book succeeds, with many first-class papers. I recommend the book to practitioners in the field, as well as those pursuing PhD-level studies.” (David Marshall, Computing Reviews, April, 2013)