Abstract
Fixation behavior toward persons in static scenes varies considerably between individuals. However, it is unclear whether these differences generalize to dynamic stimuli. Here, we examined individual differences in the distribution of gaze across seven person features (i.e. body and face parts) in static and dynamic scenes. Forty-four participants freely viewed 700 complex static scenes followed by eight director-cut videos (28,925 frames). We determined the presence of person features using hand-delineated pixel masks (images) and Deep Neural Networks (videos). Results replicated highly consistent individual differences in fixation tendencies for all person features in static scenes and revealed that these tendencies generalize to videos. Individual fixation behavior for both, images and videos, fell into two anticorrelated clusters representing the tendency to fixate faces versus bodies. These results corroborate a low-dimensional space for individual gaze biases toward persons and show they generalize from images to videos.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.