Acquine: Aesthetic quality inference engine - Real-time automatic rating of photo aesthetics

Ritendra Datta, James Wang

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

52 Scopus citations

Abstract

We present ACQUINE - Aesthetic Quality Inference Engine, a publicly accessible system which allows users to upload their photographs and have them rated automatically for aesthetic quality. The system integrates a support vector machine based classifier which extracts visual features on the fly and performs real-time classification and prediction. As the first publicly available tool for automatically determining the aesthetic value of an image, this work is a significant first step in recognizing human emotional reaction to visual stimulus. In this paper, we discuss fundamentals behind this system, and some of the challenges faced while creating it. We report statistics generated from over 140,000 images uploaded by Web users. The system is demonstrated at http://acquine.alipr.com.

Original languageEnglish (US)
Title of host publicationMIR 2010 - Proceedings of the 2010 ACM SIGMM International Conference on Multimedia Information Retrieval
Pages421-424
Number of pages4
DOIs
StatePublished - 2010
Event2010 ACM SIGMM International Conference on Multimedia Information Retrieval, MIR 2010 - Philadelphia, PA, United States
Duration: Mar 29 2010Mar 31 2010

Other

Other2010 ACM SIGMM International Conference on Multimedia Information Retrieval, MIR 2010
CountryUnited States
CityPhiladelphia, PA
Period3/29/103/31/10

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Information Systems

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    Datta, R., & Wang, J. (2010). Acquine: Aesthetic quality inference engine - Real-time automatic rating of photo aesthetics. In MIR 2010 - Proceedings of the 2010 ACM SIGMM International Conference on Multimedia Information Retrieval (pp. 421-424) https://doi.org/10.1145/1743384.1743457