We propose a novel approach for First Impressions Recognition in terms of the Big Five personality-traits from short videos. The Big Five personality traits is a model to describe human personality using five broad categories: Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness. We train two bi-modal end-to-end deep neural network architectures using temporally ordered audio and novel stochastic visual features from few frames, without over-fitting. We empirically show that the trained models perform exceptionally well, even after training from a small sub-portions of inputs. Our method is evaluated in ChaLearn LAP 2016 Apparent Personality Analysis (APA) competition using ChaLearn LAP APA2016 dataset and achieved excellent performance.
@article{arxiv.1610.10048,
title = {Bi-modal First Impressions Recognition using Temporally Ordered Deep Audio and Stochastic Visual Features},
author = {Arulkumar Subramaniam and Vismay Patel and Ashish Mishra and Prashanth Balasubramanian and Anurag Mittal},
journal= {arXiv preprint arXiv:1610.10048},
year = {2016}
}
Comments
to be published in: ECCV 2016 Workshops proceedings (Apparent Personality Analysis)