Overview
- 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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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.
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Keywords
- 3D Reconstruction
- Boosting
- Computer Vision
- Convex Optimization
- Event and Activity Recognition
- Graph Cuts
- Image Segmentation
- Image and Video Analysis
- Large Scale Image Classification
- Learning Objects
- Loopy Belief Propagation
- Message Parsing
- Metric Learning
- Object Detection
- Scene Understanding
- Stereo Matching
- Super Resolution
- Visual Features
Table of contents (14 chapters)
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Front Matter
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Back Matter
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
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