Toward Interactively Balancing the Screen Time of Actors Based on Observable Phenotypic Traits in Live Telecast

Md Naimul Hoque, Nazmus Saquib, Syed Masum Billah, Klaus Mueller

Research output: Contribution to journalArticlepeer-review

Abstract

Several prominent studies have shown that the imbalanced on-screen exposure of observable phenotypic traits like gender and skin-tone in movies, TV shows, live telecasts, and other visual media can reinforce gender and racial stereotypes in society. Researchers and human rights organizations alike have long been calling to make media producers more aware of such stereotypes. While awareness among media producers is growing, balancing the presence of different phenotypes in a video requires substantial manual effort and can typically only be done in the post-production phase. The task becomes even more challenging in the case of a live telecast where video producers must make instantaneous decisions with no post-production phase to refine or revert a decision. In this paper, we propose Screen-Balancer, an interactive tool that assists media producers in balancing the presence of different phenotypes in a live telecast. The design of Screen-Balancer is informed by a field study conducted in a professional live studio. Screen-Balancer analyzes the facial features of the actors to determine phenotypic traits using facial detection packages; it then facilitates real-time visual feedback for interactive moderation of gender and skin-tone distributions. To demonstrate the effectiveness of our approach, we conducted a user study with 20 participants and asked them to compose live telecasts from a set of video streams simulating different camera angles, and featuring several male and female actors with different skin-tones. The study revealed that the participants were able to reduce the difference of screen times of male and female actors by 43%, and that of light-skinned and dark-skinned actors by 44%, thus showing the promise and potential of using such a tool in commercial production systems.

Original languageEnglish (US)
Article number154
JournalProceedings of the ACM on Human-Computer Interaction
Volume4
Issue numberCSCW2
DOIs
StatePublished - Oct 14 2020

All Science Journal Classification (ASJC) codes

  • Social Sciences (miscellaneous)
  • Human-Computer Interaction
  • Computer Networks and Communications

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