Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3489849.3489925acmconferencesArticle/Chapter ViewAbstractPublication PagesvrstConference Proceedingsconference-collections
abstract

Exploring Emotion Brushes for a Virtual Reality Painting Tool

Published: 08 December 2021 Publication History

Abstract

We present emoPaint, a virtual reality application that allows users to create paintings with expressive emotion-based brushes and shapes. While previous systems have introduced painting in 3D space, emoPaint focuses on supporting emotional characteristics by allowing users to use brushes corresponding to specific emotions or to create their own emotion brushes and paint with the corresponding visual elements. Our system provides a variety of line textures, shape representations and color palettes for each emotion to enable users to control expression of emotions in their paintings. In this work we describe our implementation and illustrate paintings created using emoPaint.

Supplementary Material

MP4 File (VRSTposter_JungahS.mp4)
Supplemental video

References

[1]
Xavier Alameda-Pineda, Elisa Ricci, Yan Yan, and Nicu Sebe. 2016. Recognizing emotions from abstract paintings using non-linear matrix completion. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 5240–5248.
[2]
AZquotes. [n.d.]. TOP 25 quotes BY EUGENE Delacroix (of 92): A-Z Quotes. Retrieved August 10, 2021 from https://www.azquotes.com/author/3832-Eugene_Delacroix
[3]
Hyojin Bahng, Seungjoo Yoo, Wonwoong Cho, David Keetae Park, Ziming Wu, Xiaojuan Ma, and Jaegul Choo. 2018. Coloring with words: Guiding image colorization through text-based palette generation. In Proceedings of the european conference on computer vision (eccv). 431–447.
[4]
Andrea Brykoca. 2016. Part 1, Project 1, Exercise 1: Expressive lines and marks. Retrieved October 8, 2021 from https://andreabrykoca.wordpress.com/2015/02/10/project-1-exercise-1-expressive-lines-and-marks/
[5]
Jaime Crehan. 2016. Experimenting with expressive lines and marks. Retrieved October 8, 2021 from https://jaimecrehandrawing.wordpress.com/category/coursework/project-1/exercise-1-experimenting-with-expressive-lines-and-marks/
[6]
Marianne Dorn. 2019. Line and emotion: a warm-up exercise. Retrieved October 8, 2021 from http://art2art.org.uk/blog/line-and-emotion-a-warm-up-exercise
[7]
Paul Ekman. 1992. Facial expressions of emotion: New findings, new questions.
[8]
Robert Enoch. 2014. Expressive lines and marks. Retrieved October 8, 2021 from https://cat513511.wordpress.com/2014/10/28/expressive-lines-and-marks/
[9]
Meryl Grung. 2014. Exercise 1 – Expressive lines and marks. Retrieved October 8, 2021 from https://merylgrung.wordpress.com/2014/10/09/exercise-1-expressive-lines-and-marks/
[10]
Jesús Ibáñez and Carlos Delgado-Mata. 2013. Can the same visual modality express arousal or valence depending on the other modalities it is combined with?Procedia Technology 7(2013), 424–435.
[11]
Angela Johnson. 2015. Project 1. Exercise 1. Expressive lines and marks. Retrieved October 8, 2021 from https://drawingangel.wordpress.com/2015/02/05/exercise-1-expressive-lines-and-marks/
[12]
Junghyun Lee, Jongin Choi, and Sanghyun Seo. 2020. Emotion-inspired painterly rendering. IEEE Access 8(2020), 104565–104578.
[13]
Jana Machajdik and Allan Hanbury. 2010. Affective image classification using features inspired by psychology and art theory. In Proceedings of the 18th ACM international conference on Multimedia. 83–92.
[14]
Sabina Radeva. 2017. Exercise 1: Experimenting with expressive lines and marks. Retrieved October 8, 2021 from https://www.sabinaradeva.com/drawing-1-blog/2017/10/15/exercise-1-experimenting-with-expressive-lines-and-marks
[15]
James A Russell. 1980. A circumplex model of affect.Journal of personality and social psychology 39, 6(1980), 1161.
[16]
Infographic Design Team. 2019. 7 Paramount Components of Visual Communication. Retrieved August 10, 2021 from https://www.infographicdesignteam.com/blog/components-of-visual-communication/
[17]
Sicheng Zhao, Yue Gao, Xiaolei Jiang, Hongxun Yao, Tat-Seng Chua, and Xiaoshuai Sun. 2014. Exploring principles-of-art features for image emotion recognition. In Proceedings of the 22nd ACM international conference on Multimedia. 47–56.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
VRST '21: Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology
December 2021
563 pages
ISBN:9781450390927
DOI:10.1145/3489849
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 December 2021

Check for updates

Qualifiers

  • Abstract
  • Research
  • Refereed limited

Conference

VRST '21

Acceptance Rates

Overall Acceptance Rate 66 of 254 submissions, 26%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 201
    Total Downloads
  • Downloads (Last 12 months)45
  • Downloads (Last 6 weeks)3
Reflects downloads up to 01 Nov 2024

Other Metrics

Citations

View Options

Get Access

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media