Intelligent portrait composition assistance: Integrating deep-learned models and photography idea retrieval

Farshid Farhat, Mohammad Mahdi Kamani, Sahil Mishra, James Z. Wang

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

2 Scopus citations

Abstract

Retrieving photography ideas corresponding to a given location facilitates the usage of smart cameras, where there is a high interest among amateurs and enthusiasts to take astonishing photos at anytime and in any location. Existing research captures some aesthetic techniques and retrieves useful feedbacks based on one technique. However, they are restricted to a particular technique and the retrieved results have room to improve as they are confined to the quality of the query. There is a lack of a holistic framework to capture important aspects of a given scene and help a novice photographer by informative feedback to take a be.er shot in his/her photography adventure. This work proposes an intelligent framework of portrait composition using our deep-learned models and image retrieval methods. A highly-rated web-crawled portrait dataset is exploited for retrieval purposes. Our framework detects and extracts ingredients of a given scene representing as a correlated semantic model. It then matches extracted semantics with the dataset of aesthetically composed photos to investigate a ranked list of photography ideas, and gradually optimizes the human pose and other artistic aspects of the composed scene supposed to be captured. The conducted user study demonstrates that our approach is more helpful than other feedback retrieval systems.

Original languageEnglish (US)
Title of host publicationThematic Workshops 2017 - Proceedings of the Thematic Workshops of ACM Multimedia 2017, co-located with MM 2017
PublisherAssociation for Computing Machinery, Inc
Pages17-25
Number of pages9
ISBN (Electronic)9781450354165
DOIs
StatePublished - Oct 23 2017
Event1st International ACM Thematic Workshops, Thematic Workshops 2017 - Mountain View, United States
Duration: Oct 23 2017Oct 27 2017

Publication series

NameThematic Workshops 2017 - Proceedings of the Thematic Workshops of ACM Multimedia 2017, co-located with MM 2017

Other

Other1st International ACM Thematic Workshops, Thematic Workshops 2017
CountryUnited States
CityMountain View
Period10/23/1710/27/17

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computational Theory and Mathematics
  • Theoretical Computer Science

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    Farhat, F., Kamani, M. M., Mishra, S., & Wang, J. Z. (2017). Intelligent portrait composition assistance: Integrating deep-learned models and photography idea retrieval. In Thematic Workshops 2017 - Proceedings of the Thematic Workshops of ACM Multimedia 2017, co-located with MM 2017 (pp. 17-25). (Thematic Workshops 2017 - Proceedings of the Thematic Workshops of ACM Multimedia 2017, co-located with MM 2017). Association for Computing Machinery, Inc. https://doi.org/10.1145/3126686.3126710