Advanced Topics in Computer Vision

Giovanni Maria Farinella

ISBN 10: 144715519X / ISBN 13: 9781447155195

Edité par Springer London, Springer London, 2013

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - 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.

N° de réf. du vendeur 9781447155195

Détails bibliographiques

• Titre: Advanced Topics in Computer Vision
• Éditeur: Springer London, Springer London
• Date de parution: 2013
• Langue: anglais
• ISBN à 10 chiffres: 144715519X
• ISBN à 13 chiffres: 9781447155195
• Reliure: Buch
• État de l'article: Neu

A propos de ce titre

Synopsis

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.

À propos de l?auteur

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.