Assessing Personally Perceived Image Quality via Image Features and Collaborative Filtering

Jari Korhonen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

9 Citations (Scopus)

Abstract

During the past few years, different methods for optimizing the camera settings and post-processing techniques to improve the subjective quality of consumer photos have been studied extensively. However, most of the research in the priorart has focused on finding the optimal method for an average user. Since there is large deviation in personal opinions and aesthetic standards, the next challenge is to find the settings and post-processing techniques thatfit to the individualusers 'personaltaste. In this study, we aim to predict the personallyperceived image quality by combining classical imagefeature analysis and collaboration filtering approach known from the recommendation systems. The experimental resultsfor the proposed method show promising results. As a practical application, our work can be used for personalizing the camera settings orpost-processingparameterfsor different users and images.

Original languageEnglish
Title of host publication2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
PublisherIEEE Explore
Pages8161-8169
Number of pages9
DOIs
Publication statusPublished - 2019
EventIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) - Long Beach, Canada
Duration: 16 Jun 201920 Jun 2019

Conference

ConferenceIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Country/TerritoryCanada
CityLong Beach
Period16/06/1920/06/19

Bibliographical note

ACKNOWLEDGEMENTS
This work was supported in part by the National Science Foundation of China under Grant 61772348.

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