Computer Vision

1. Front Matter

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2. Is Human Vision Any Good?

   • Jan J. Koenderink

   Pages 1-25

3. Knowing a Good Feature When You See It: Ground Truth and Methodology to Evaluate Local Features for Recognition

   • Andrea Vedaldi, Haibin Ling, Stefano Soatto

   Pages 27-49

4. Dynamic Graph Cuts and Their Applications in Computer Vision

   • Pushmeet Kohli, Philip H. S. Torr

   Pages 51-108

5. Discriminative Graphical Models for Context-Based Classification

   • Sanjiv Kumar

   Pages 109-134

6. From the Subspace Methods to the Mutual Subspace Method

   • Ken-ichi Maeda

   Pages 135-156

7. What, Where and Who? Telling the Story of an Image by Activity Classification, Scene Recognition and Object Categorization

   • Li Fei-Fei, Li-Jia Li

   Pages 157-171

8. Semantic Texton Forests

   • Matthew Johnson, Jamie Shotton

   Pages 173-203

9. Multi-view Object Categorization and Pose Estimation

   • Silvio Savarese, Li Fei-Fei

   Pages 205-231

10. A Vision-Based Remote Control

    • Björn Stenger, Thomas Woodley, Roberto Cipolla

    Pages 233-262

11. Multi-view Multi-object Detection and Tracking

    • Murtaza Taj, Andrea Cavallaro

    Pages 263-280

12. Shape from Photographs: A Multi-view Stereo Pipeline

    • Carlos Hernández, George Vogiatzis

    Pages 281-311

13. Practical 3D Reconstruction Based on Photometric Stereo

    • George Vogiatzis, Carlos Hernández

    Pages 313-345

14. Back Matter

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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 first two editions of the school on topics such as Recognition, Registration and Reconstruction. The chapters provide an in-depth overview of these challenging areas with key references to the existing literature.

• Computational Intelligence
• Computer Vision
• Detection
• Ground Truth
• Layout
• Recognition
• Reconstruction
• cognition
• image processing
• robot
• robotics
• science
• technology

• Department of Engineering, University of Cambridge, Cambridge, UK

  Roberto Cipolla

• Dipartimento di Matematica ed Informatica, University of Catania, Catania, Italy

  Sebastiano Battiato, Giovanni Maria Farinella

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