Assessing the aesthetic quality of photographs through group comparison

Mei Chen Yeh*, Chun Hui Chuang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The availability and exponential growth in online media provides opportunities for understanding and responding to real world challenges. In this paper we investigate the photo quality assessment problem using a large volume of online images retrieved by Google Image Search. To effectively use the big data, we present new approaches that compute discriminative features from a group of relevant images. We also evaluate two popular regression models, support vector regression (SVR) and ranking support vector machine (RankSVM), for their effectiveness in predicting an aesthetic score from the features. Experiments using 99,000 online images provide interesting results. We examine and identify the cases in which online images facilitate the automatic rating task.

Original languageEnglish
Title of host publicationDigest of Technical Papers - IEEE International Conference on Consumer Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages91-92
Number of pages2
ISBN (Electronic)9781479938308
DOIs
Publication statusPublished - 2014 Sept 18
Externally publishedYes
Event1st IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2014 - Taipei, Taiwan
Duration: 2014 May 262014 May 28

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
ISSN (Print)0747-668X

Other

Other1st IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2014
Country/TerritoryTaiwan
CityTaipei
Period2014/05/262014/05/28

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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