Data-Driven Modeling of Group Entitativity in Virtual Environments

Emily Kubin
Emily Kubin
Husam Shaik
Husam Shaik

VRST '18: 24th ACM Symposium on Virtual Reality Software and Technology Tokyo Japan November, 2018, pp. 1-10, 2018.

Cited by: 3|Views23
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Abstract:

We present a data-driven algorithm to model and predict the socio-emotional impact of groups on observers. Psychological research finds that highly entitative i.e. cohesive and uniform groups induce threat and unease in observers. Our algorithm models realistic trajectory-level behaviors to classify and map the motion-based entitativity o...More

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