Recognizing affect from non-stylized body motion using shape of Gaussian descriptors
Liyu Gong, Tianjiang Wang, Chengshuo Wang, Fang Liu, Fuqiang Zhang, Xiaoyuan Yu · 2010
In this paper, we address the problem of recognizing affect from non-stylized human body motion. We utilize a novel feature descriptor which is based on the shape of signal probability density function framework to represent the motion capture data. Combining the feature representation scheme with support vector machine classifier, we detect implicitly communicated affect in human body motion. We test our algorithm using a comprehensive database of affectively performed motion. Experiment results show state-of-the-art performance compared with the existing methods.