Photo filter recommendation through analyzing objects, scenes and aesthetics

Yi Ning Chen, Mei Chen Yeh

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

Abstract

Photo filters are widespread - they give photos a stylized look without requiring the user to have professional knowledge of image processing. However, with the increasing number of photo filters and limited display size of mobile devices, selecting a proper filter for a given photo can be a tedious task for camera phone users. In this paper, we present a photo filter recommendation approach to address this problem. In particular, we rely on state-of-the-art deep learning approaches to extract objects, scenes, and image aesthetics reliably and represent them using deep features as the observations of our recommendation model. Furthermore, we collect 68,400 filtered photos from Instagram to learn the relationships among objects, scenes, aesthetics, and filter types. Experimental results using the FACD benchmark dataset demonstrate the state-of-the-art recommendation performance of the proposed approach; these results show that objects, scenes, and aesthetic attributes influence filter preference.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 5th International Conference on Multimedia Big Data, BigMM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages252-256
Number of pages5
ISBN (Electronic)9781728155272
DOIs
Publication statusPublished - 2019 Sep
Event5th IEEE International Conference on Multimedia Big Data, BigMM 2019 - Singapore, Singapore
Duration: 2019 Sep 112019 Sep 13

Publication series

NameProceedings - 2019 IEEE 5th International Conference on Multimedia Big Data, BigMM 2019

Conference

Conference5th IEEE International Conference on Multimedia Big Data, BigMM 2019
CountrySingapore
CitySingapore
Period19/9/1119/9/13

Keywords

  • Deep learning
  • Image aesthetics
  • Image style
  • Photo filter recommendation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Media Technology

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  • Cite this

    Chen, Y. N., & Yeh, M. C. (2019). Photo filter recommendation through analyzing objects, scenes and aesthetics. In Proceedings - 2019 IEEE 5th International Conference on Multimedia Big Data, BigMM 2019 (pp. 252-256). [8919296] (Proceedings - 2019 IEEE 5th International Conference on Multimedia Big Data, BigMM 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigMM.2019.00-16