Objectivity and Subjectivity in Aesthetic Quality Assessment of Digital Photographs

Won Hee Kim, Jun Ho Choi, Jong Seok Lee

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Automatic prediction of the aesthetic quality of a photograph has been an important research problem in image processing and computer vision. While assessing the aesthetic quality of a photograph by human is highly subjective, most existing studies have considered only objective (or general) opinion of multiple viewers. In this paper, we provide a comprehensive investigation of the issue of subjectivity in aesthetic quality assessment using a large-scale database containing photos, user ratings, and user comments. First, we analyze how the mean aesthetic quality level and the level of subjectivity have evolved over time. Second, we examine the feasibility of automatic prediction of the level of subjectivity based on visual features, and identify which features are effective for the prediction. Third, we analyze the users' comments given to photos to understand the sources of subjectivity of aesthetic quality rating. Our results show that several factors are simultaneously involved in determining the level of subjectivity of a photo, but it can be predicted with reasonable accuracy. We believe that our results provide insight toward personalized aesthetic photo applications.

Original languageEnglish
Article number8302852
Pages (from-to)493-506
Number of pages14
JournalIEEE Transactions on Affective Computing
Volume11
Issue number3
DOIs
Publication statusPublished - 2020 Jul 1

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction

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