학술논문

Bridging computer vision and social science: A multi-camera vision system for social interaction training analysis
Document Type
Conference
Source
2015 IEEE International Conference on Image Processing (ICIP) Image Processing (ICIP), 2015 IEEE International Conference on. :823-826 Sep, 2015
Subject
Computing and Processing
Signal Processing and Analysis
Training
Visualization
Cameras
Computer vision
Machine vision
Estimation
Correlation
social interaction
social signal processing
gaze
facial expression
body pose
behavior analysis
Language
Abstract
We investigate the use of a vision-based system capable of estimating social states such as rapport and hostility. We study the correlation between interpretations automatically generated by our system and those reported by social scientists. Our multi-camera vision system collects visual cues including location (proximity), motion, pose, gaze, and facial expressions in real-time from multiple subjects moving freely in an unconstrained environment. We performed experiments on 80+ subjects. Preliminary regression analysis suggests high correlation between machine distilled time series signals and assessments made by human experts.