Advanced Topics in Computer Vision

Zusatztext

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.

Autorenportrait

<b>Dr. Giovanni Maria Farinella</b> 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. <b>Dr.</b> <b>Sebastiano Battiato</b> is Associate Professor at the University of Catania, Italy. <b>Dr. Roberto Cipolla</b> is Professor of Information Engineeringat the University of Cambridge, UK.

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