Preliminary communication
https://doi.org/10.21860/j.13.1.11
Labelling the psychological impact of colour in films for deep learning processing based on the humanities approach: RGB information in colour classification in film
Youngsue Han
; The Interpretation and Translation of the German Language, Hankuk University of Foreign Studies, Seoul, South Korea
Hyunjung Roh
; Education Technology, Sogang University, Seoul, South Korea
Thomas Whelan
; Korean Studies, Hankuk University of Foreign Studies, Seoul, South Korea
Suhyoun Hwang
orcid.org/0000-0002-2467-0354
; Bioinformation & Statistics, Korea National Open University, Seoul, South Korea
Minju Kim
; English Linguistics & Language Technology, Hankuk University of Foreign Studies, Seoul, South Korea
Abstract
Inspired by Goethe’s theory of colour and his aversion to Newton’s scientific theories, we performed an experiment to investigate the psychological impact of colour in film. We converted 550 films into sequences of images and then processed them to extract the RGB information within. We then compared this data and matched them to classifications of colour roles in terms of their psychological influence on film viewers. For this we consulted Bellantoni, Patti (2005)’s book If It’s Purple, Someone’s Gonna Die: The Power Of Colour In Visual Storytelling, which is a guide for filmmakers to select the appropriate colours for their films and also describes the psychological and emotional effects of certain colours in film on viewers. Finally we extracted RGB information from our image sequence archives to match them to classifications of the role of colour and their psychological influences on film viewers. In spite of the fact that our results are subject to certain limitations such as the subjectivity of our researchers, we believe our findings from the experiment have made contributions to the development of AI for use in film colour classification with regard to their psychological impacts on viewers. In future endeavors, we expect to include additional information, such as shapes, tints and so on. Thus, our methodology and materials may produce even better results if supplementary resources were to be available.
Keywords
Goethe; colour; deep learning; film; RGB
Hrčak ID:
281564
URI
Publication date:
30.8.2022.
Visits: 1.440 *