research-article

CAPTAIN: Comprehensive Composition Assistance for Photo Taking

Authors:

Farshid Farhat,

Mohammad Mahdi Kamani,

James Z. WangAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 18, Issue 1

Article No.: 14, Pages 1 - 24

https://doi.org/10.1145/3462762

Published: 27 January 2022 Publication History

Abstract

Many people are interested in taking astonishing photos and sharing them with others. Emerging high-tech hardware and software facilitate the ubiquitousness and functionality of digital photography. Because composition matters in photography, researchers have leveraged some common composition techniques, such as the rule of thirds and the perspective-related techniques, in providing photo-taking assistance. However, composition techniques developed by professionals are far more diverse than well-documented techniques can cover. We present a new approach to leverage the underexplored photography ideas, which are virtually unlimited, diverse, and correlated. We propose a comprehensive fork-join framework, named CAPTAIN (Composition Assistance for Photo Taking), to guide a photographer with a variety of photography ideas. The framework consists of a few components: integrated object detection, photo genre classification, artistic pose clustering, and personalized aesthetics-aware image retrieval. CAPTAIN is backed by a large managed dataset crawled from a Website with ideas from photography enthusiasts and professionals. The work proposes steps to decompose a given amateurish shot into composition ingredients and compose them to bring the photographer a list of useful and related ideas. The work addresses personal preferences for composition by presenting a user-specified preference list of photography ideas. We have conducted many experiments on the newly proposed components and reported findings. A user study demonstrates that the work is useful to those taking photos.

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Cited By

Götz-Hahn FWong LHosu V(2023)The Inter-Relationship Between Photographic Aesthetics and Technical QualityModeling Visual Aesthetics, Emotion, and Artistic Style10.1007/978-3-031-50269-9_14(231-255)Online publication date: 25-Nov-2023
https://doi.org/10.1007/978-3-031-50269-9_14
Li JShe YLiu FYu CWang XXu Y(2022)Augmented Reality Based Video Shooting Guidance for Novice UsersProceedings of the ACM on Human-Computer Interaction10.1145/35467506:MHCI(1-20)Online publication date: 20-Sep-2022
https://dl.acm.org/doi/10.1145/3546750

Index Terms

CAPTAIN: Comprehensive Composition Assistance for Photo Taking
1. Applied computing
  1. Arts and humanities
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object detection
      2. Image and video acquisition
        Computational photography

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 18, Issue 1

January 2022

517 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3505205

Editor:
Alberto Del Bimbo
University of Firenze, Italy

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Publication History

Published: 27 January 2022

Accepted: 01 April 2021

Revised: 01 April 2021

Received: 01 May 2020

Published in TOMM Volume 18, Issue 1

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Cited By

Götz-Hahn FWong LHosu V(2023)The Inter-Relationship Between Photographic Aesthetics and Technical QualityModeling Visual Aesthetics, Emotion, and Artistic Style10.1007/978-3-031-50269-9_14(231-255)Online publication date: 25-Nov-2023
https://doi.org/10.1007/978-3-031-50269-9_14
Li JShe YLiu FYu CWang XXu Y(2022)Augmented Reality Based Video Shooting Guidance for Novice UsersProceedings of the ACM on Human-Computer Interaction10.1145/35467506:MHCI(1-20)Online publication date: 20-Sep-2022
https://dl.acm.org/doi/10.1145/3546750

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