Audience Understanding

Audience Understanding is a multidisciplinary effort—combining computer vision, machine learning, and experimental psychology—to gain deeper insight into how audiences engage with entertainment experiences.



Understanding the audience experience requires not only an appreciation of how emotional states manifest in behavior—such as body motion, facial expressions, and patterns of eye movement—but also a comprehensive view of how content is produced with an intent to induce certain emotional states.  Narrative experiences aim to take audiences on an emotional journey.  Our research is focused on understanding whether that intended journey is being taken.  Our approach uses cutting-edge computer-vision methods for interpreting the behavior of volunteer audiences and machine-learning models for analyzing content for its structure and creative intent.  The result is a tool for both executives and creatives that allows for a better moment-to-moment understanding of how audiences relate to the Disney experience.


Tech Transfer:

Insights from the Audience Understanding project are being used by the Disney-ABC Television Group to inform content decisions.

Publication Highlights

Predicting Movie Ratings from Audience Behaviors

March 24, 2016
IEEE Winter Conference on Applications of Computer Vision

Rajitha Navarathna (Disney Research/Queensland University of Technology) Patrick Lucey (Disney Research) Peter Carr (Disney Research) Elizabeth Carter (Carnegie Mellon University) Sridha Sridharan (Queensland University of Technology) Iain Matthews (Disney Research)