Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikace
ČADÍK, M. HERZOG, R. MANTIUK, R. MANTIUK, R. MYSZKOWSKI, K. SEIDEL, H.
Originální název
Learning to Predict Localized Distortions in Rendered Images
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
In this work, we present an analysis of feature descriptors for objective image quality assessment. We explore a large space of possible features including components of existing image quality metrics as well as many traditional computer vision and statistical features. Additionally, we propose new features motivated by human perception and we analyze visual saliency maps acquired using an eye tracker in our user experiments. The discriminative power of the features is assessed by means of a machine learning framework revealing the importance of each feature for image quality assessment task. Furthermore, we propose a new data-driven full-reference image quality metric which outperforms current state-of-the-art metrics. The metric was trained on subjective ground truth data combining two publicly available datasets. For the sake of completeness we create a new testing synthetic dataset including experimentally measured subjective distortion maps. Finally, using the same machine-learning framework we optimize the parameters of popular existing metrics.
Klíčová slova
image quality assessment, feature vectors, machine learning, rendering
Autoři
ČADÍK, M.; HERZOG, R.; MANTIUK, R.; MANTIUK, R.; MYSZKOWSKI, K.; SEIDEL, H.
Rok RIV
2013
Vydáno
1. 11. 2013
ISSN
0167-7055
Periodikum
COMPUTER GRAPHICS FORUM
Ročník
Číslo
7
Stát
Spojené království Velké Británie a Severního Irska
Strany od
401
Strany do
410
Strany počet
10
URL
http://cadik.posvete.cz
BibTex
@article{BUT103580, author="Martin {Čadík} and Robert {Herzog} and Rafał {Mantiuk} and Radosław {Mantiuk} and Karol {Myszkowski} and Hans-Peter {Seidel}", title="Learning to Predict Localized Distortions in Rendered Images", journal="COMPUTER GRAPHICS FORUM", year="2013", volume="2013", number="7", pages="401--410", doi="10.1111/cgf.12248", issn="0167-7055", url="http://cadik.posvete.cz" }