Automatic personality prediction from audiovisual data using random forest regression

In this paper, we focus on describing the method we designed for automatic perceived personality prediction. We present a simple model that uses three different sets of features: nonverbal audio cues, visual cues from video, and facial landmark points. The model uses a random decision forest to do regression from the extracted features. As we discuss in Section 4, this multimodal model performs relatively well in the task of personality analysis and recognition of certain personality traits from short video clips. Using this model, we came in 4th place in the first track of the second round of Joint Contest on Multimedia Challenges Beyond Visual Analysis at ICPR 2016 [1].