Xu / Lin / Kuo Visual Quality Assessment by Machine Learning

1. Auflage 2015
ISBN: 978-981-287-468-9
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 132 Seiten

Reihe: SpringerBriefs in Electrical and Computer Engineering

The book encompasses the state-of-the-art visual quality assessment (VQA) and learning based visual quality assessment (LB-VQA) by providing a comprehensive overview of the existing relevant methods. It delivers the readers the basic knowledge, systematic overview and new development of VQA. It also encompasses the preliminary knowledge of Machine Learning (ML) to VQA tasks and newly developed ML techniques for the purpose. Hence, firstly, it is particularly helpful to the beginner-readers (including research students) to enter into VQA field in general and LB-VQA one in particular. Secondly, new development in VQA and LB-VQA particularly are detailed in this book, which will give peer researchers and engineers new insights in VQA.

Zielgruppe

Research

Autoren/Hrsg.

Xu, Long

Lin, Weisi

Kuo, C.-C. Jay

Inhaltsverzeichnis

Introduction.- Fundamental knowledges of machine learning.- Image features and feature processing.- Feature pooling by learning.- Metrics fusion.- Summary and remarks for future research.