Being the Center of Attention

Author:

Dotti Dario1,Popa Mirela1,Asteriadis Stylianos1

Affiliation:

1. Maastricht University, The Netherlands, EN

Abstract

This article proposes a novel study on personality recognition using video data from different scenarios. Our goal is to jointly model nonverbal behavioral cues with contextual information for a robust, multi-scenario, personality recognition system. Therefore, we build a novel multi-stream Convolutional Neural Network (CNN) framework, which considers multiple sources of information. From a given scenario, we extract spatio-temporal motion descriptors from every individual in the scene, spatio-temporal motion descriptors encoding social group dynamics, and proxemics descriptors to encode the interaction with the surrounding context. All the proposed descriptors are mapped to the same feature space facilitating the overall learning effort. Experiments on two public datasets demonstrate the effectiveness of jointly modeling the mutual Person-Context information, outperforming the state-of-the art-results for personality recognition in two different scenarios. Last, we present CNN class activation maps for each personality trait, shedding light on behavioral patterns linked with personality attributes.

Funder

European Union’ Horizon 2020 Research and Innovation Programme

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Co-Located Human–Human Interaction Analysis Using Nonverbal Cues: A Survey;ACM Computing Surveys;2023-11-25

2. Personality in Daily Life: Multi-Situational Physiological Signals Reflect Big-Five Personality Traits;IEEE Journal of Biomedical and Health Informatics;2023-06

3. Psychology-Inspired Interaction Process Analysis based on Time Series;2022 26th International Conference on Pattern Recognition (ICPR);2022-08-21

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