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Advanced Topics in Computer Vision

  • Book
  • © 2013

Overview

Editors:
  1. Giovanni Maria Farinella

    1. Dipartimento di Matematica e Informatica, Università di Catania, Catania, Italy

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  2. Sebastiano Battiato

    1. Dipartimento di Matematica e Informatica, Università di Catania, Catania, Italy

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  3. Roberto Cipolla

    1. Department of Engineering, University of Cambridge, Cambridge, United Kingdom

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  • Presents a broad selection of cutting-edge research from internationally-recognized computer vision groups
  • Covers both theoretical and practical aspects of reconstruction, registration, and recognition
  • Provides an overview of challenging areas, and describes novel algorithms designed to infer the semantic content of images and videos
  • Includes supplementary material: sn.pub/extras

Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)

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Table of contents (14 chapters)

  1. Front Matter

    Pages I-XIV
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  2. Visual Features—From Early Concepts to Modern Computer Vision

    • Martin Weinmann
    Pages 1-34

  3. Where Next in Object Recognition and how much Supervision Do We Need?

    • Sandra Ebert, Bernt Schiele
    Pages 35-64

  4. Recognizing Human Actions by Using Effective Codebooks and Tracking

    • Lamberto Ballan, Lorenzo Seidenari, Giuseppe Serra, Marco Bertini, Alberto Del Bimbo
    Pages 65-93

  5. Evaluating and Extending Trajectory Features for Activity Recognition

    • Ross Messing, Atousa Torabi, Aaron Courville, Chris Pal
    Pages 95-111

  6. Co-recognition of Images and Videos: Unsupervised Matching of Identical Object Patterns and Its Applications

    • Minsu Cho, Young Min Shin, Kyoung Mu Lee
    Pages 113-141

  7. Stereo Matching—State-of-the-Art and Research Challenges

    • Michael Bleyer, Christian Breiteneder
    Pages 143-179

  8. Visual Localization for Micro Aerial Vehicles in Urban Outdoor Environments

    • Andreas Wendel, Horst Bischof
    Pages 181-214

  9. Moment Constraints in Convex Optimization for Segmentation and Tracking

    • Maria Klodt, Frank Steinbrücker, Daniel Cremers
    Pages 215-242

  10. Large Scale Metric Learning for Distance-Based Image Classification on Open Ended Data Sets

    • Thomas Mensink, Jakob Verbeek, Florent Perronnin, Gabriela Csurka
    Pages 243-276

  11. Top–Down Bayesian Inference of Indoor Scenes

    • Luca Del Pero, Kobus Barnard
    Pages 277-311

  12. Efficient Loopy Belief Propagation Using the Four Color Theorem

    • Radu Timofte, Luc Van Gool
    Pages 313-339

  13. Boosting k-Nearest Neighbors Classification

    • Paolo Piro, Richard Nock, Wafa Bel Haj Ali, Frank Nielsen, Michel Barlaud
    Pages 341-375

  14. Learning Object Detectors in Stationary Environments

    • Peter M. Roth, Sabine Sternig, Horst Bischof
    Pages 377-409

  15. Video Temporal Super-resolution Based on Self-similarity

    • Mihoko Shimano, Takahiro Okabe, Imari Sato, Yoichi Sato
    Pages 411-430

  16. Back Matter

    Pages 431-433
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Keywords

About this book

This book presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of reconstruction, registration, and recognition. The text provides an overview of challenging areas and descriptions of novel algorithms. Features: investigates visual features, trajectory features, and stereo matching; reviews the main challenges of semi-supervised object recognition, and a novel method for human action categorization; presents a framework for the visual localization of MAVs, and for the use of moment constraints in convex shape optimization; examines solutions to the co-recognition problem, and distance-based classifiers for large-scale image classification; describes how the four-color theorem can be used for solving MRF problems; introduces a Bayesian generative model for understanding indoor environments, and a boosting approach for generalizing the k-NN rule; discusses the issue of scene-specific object detection, and an approach for making temporal super resolution video.

Reviews

From the book reviews:

“The goal of this book is to provide an overview of recent works in computer vision. … The book is intended more for engineers and researchers who will use it as a relevant source of knowledge in the computer vision field, and benefit from the presence of recent and representative methods that are among the best existing solutions to solve the problems reviewed in the book.” (Sebastien Lefevre, Computing Reviews, June, 2014)

Editors and Affiliations

  • Dipartimento di Matematica e Informatica, Università di Catania, Catania, Italy

    Giovanni Maria Farinella, Sebastiano Battiato

  • Department of Engineering, University of Cambridge, Cambridge, United Kingdom

    Roberto Cipolla

About the editors

Dr. Giovanni Maria Farinella is Adjunct Professor of Computer Science at the University of Catania, Italy, and Contract Professor of Computer Vision at the School of Arts of Catania, Italy. Dr. Sebastiano Battiato is Associate Professor at the University of Catania, Italy. Dr. Roberto Cipolla is Professor of Information Engineeringat the University of Cambridge, UK.

Bibliographic Information

  • Book Title: Advanced Topics in Computer Vision

  • Editors: Giovanni Maria Farinella, Sebastiano Battiato, Roberto Cipolla

  • Series Title: Advances in Computer Vision and Pattern Recognition

  • DOI: https://doi.org/10.1007/978-1-4471-5520-1

  • Publisher: Springer London

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag London 2013

  • Hardcover ISBN: 978-1-4471-5519-5Published: 07 October 2013

  • Softcover ISBN: 978-1-4471-7025-9Published: 23 August 2016

  • eBook ISBN: 978-1-4471-5520-1Published: 24 September 2013

  • Series ISSN: 2191-6586

  • Series E-ISSN: 2191-6594

  • Edition Number: 1

  • Number of Pages: XIV, 433

  • Number of Illustrations: 38 b/w illustrations, 180 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics

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