TY - JOUR
T1 - CAPTAIN
T2 - Comprehensive Composition Assistance for Photo Taking
AU - Farhat, Farshid
AU - Kamani, Mohammad Mahdi
AU - Wang, James Z.
N1 - Funding Information:
This work used the Extreme Science and Engineering Discovery Environment (XSEDE) supported by National Science Foundation grant number ACI-1548562. Authors’ addresses: F. Farhat, School of Electrical Engineering and Computer Science, The Pennsylvania State University, 207 Electrical Engineering West, University Park, PA 16802; email: fuf111@psu.edu; M. M. Kamani and J. Z. Wang, College of Information Sciences and Technology, The Pennsylvania State University, E397 Westgate Building, University Park, PA 16802; emails: mqk5591@psu.edu, jwang@ist.psu.edu. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2022 Association for Computing Machinery. 1551-6857/2022/01-ART14 $15.00 https://doi.org/10.1145/3462762
Publisher Copyright:
© 2022 Association for Computing Machinery.
PY - 2022/1
Y1 - 2022/1
N2 - 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.
AB - 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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U2 - 10.1145/3462762
DO - 10.1145/3462762
M3 - Article
AN - SCOPUS:85127904398
SN - 1551-6857
VL - 18
JO - ACM Transactions on Multimedia Computing, Communications and Applications
JF - ACM Transactions on Multimedia Computing, Communications and Applications
IS - 1
M1 - 14
ER -