Affiliation:
1. Stanford University, Stanford CA
Abstract
Film directors are masters at controlling what we look at when we watch a film. However, there have been few quantitative studies of how gaze responds to cinematographic conventions thought to influence attention. We have collected and are releasing a dataset designed to help investigate eye movements in response to higher level features such as faces, dialogue, camera movements, image composition, and edits. The dataset, which will be released to the community, includes gaze information for 21 viewers watching 15 clips from live action 2D films, which have been hand annotated for high level features. This work has implications for the media studies, display technology, immersive reality, and human cognition.
Funder
Stanford's Google Graduate Fellowship Fund and NSF
Publisher
Association for Computing Machinery (ACM)
Subject
Experimental and Cognitive Psychology,General Computer Science,Theoretical Computer Science
Cited by
16 articles.
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