Perception of Human Interaction Based on Motion Trajectories: From Aerial Videos to Decontextualized Animations
Abstract
People are adept at perceiving interactions from movements of simple shapes, but the underlying mechanism remains unknown. Previous studies have often used object movements defined by experimenters. The present study used aerial videos recorded by drones in a real‐life environment to generate decontextualized motion stimuli. Motion trajectories of displayed elements were the only visual input. We measured human judgments of interactiveness between two moving elements and the dynamic change in such judgments over time. A hierarchical model was developed to account for human performance in this task. The model represents interactivity using latent variables and learns the distribution of critical movement features that signal potential interactivity. The model provides a good fit to human judgments and can also be generalized to the original Heider–Simmel animations (1944). The model can also synthesize decontextualized animations with a controlled degree of interactiveness, providing a viable tool for studying animacy and social perception.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 07, 2017
- Source ID
- 10.1111/tops.12313
Entities
People
- Hongjing Lu
- Lifeng Fan
- Song-Chun Zhu
- Tianmin Shu
- Yujia Peng
Organizations
- China Scholarship Council
- Defense Advanced Research Projects Agency
- National Science Foundation
- Office of Naval Research
- University of California, Los Angeles