Detailansicht
Advanced Topics in Computer Vision
Advances in Computer Vision and Pattern Recognition
ISBN/EAN: 9781447170259
Umbreit-Nr.: 9730963
Sprache:
Englisch
Umfang: xiv, 433 S., 38 s/w Illustr., 180 farbige Illustr.
Format in cm:
Einband:
kartoniertes Buch
Erschienen am 23.08.2016
Auflage: 1/2013
- 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.
- Kurztext
- 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. This unique text/reference presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of the three main areas in computer vision: reconstruction, registration, and recognition. The book provides an in-depth overview of challenging areas, in addition to descriptions of novel algorithms that exploit machine learning and pattern recognition techniques to infer the semantic content of images and videos. Topics and features: - Investigates visual features, trajectory features, and stereo matching Reviews the main challenges of semisupervised 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 corecognition problem, and distancebased classifiers for largescale image classification Describes how the fourcolor theorem can be used in early computer vision for solving MRF problems where an energy is to be minimized Introduces a Bayesian generative model for understanding indoor environments, and a boosting approach for generalizing the kNN rule Discusses the issue of scenespecific object detection, and an approach for making temporal super resolution video from a single input image sequence This mustread collection will be of great value to advanced undergraduate and graduate students of computer vision, pattern recognition and machine learning. Researchers and practitioners will also find the book useful for understanding and reviewing current approaches in computer vision.
- Autorenportrait
- 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.