# name
Deep learning for non-verbal personality analysis

# metadata.dc.description[].value
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2016, Director: Sergio Escalera Guerrero

# metadata.dc.description.abstract[].value
[en] In this project, we present an up-to-date review of existing computer-vision based visual and multimodal approaches for apparent personality trait recognition and analysis. We describe main works and discuss their main features as well as future lines of research in the field. Current datasets and challenges organized to push the research in the field are also discussed. We also show which visual (face, body, and background regions) and audio features (speech properties) current CNN-based methods learn in order to discriminate among the Big Five personality traits in short video clips. In addition, we present a new web-based application users can interact with, in order to receive automatic feedback about their apparent personality and relating it to five different job profiles. This application was presented as a demonstrator at NIPS 2016.

# metadata.dc.rights[].value
memòria: cc-by-nc-sa (c) Marc Pérez Quintana, 2017

# metadata.dc.source[].value
Treballs Finals de Grau (TFG) - Enginyeria Informàtica

# metadata.dc.title[].value
Deep learning for non-verbal personality analysis