# EmoCam—Capturing Emotions Using Non-Invasive Technologies

## Abstract — BSc thesis

Affective computing uses human emotions to adapt applications to users’ moods, affections and behavior. Measuring these emotions is often challenging due mainly the invasiveness of the technology needed for emotion’s sensing. Novel approaches based on non-invasive approaches utilize computer vision and machine learning algorithms to recognize emotions and facial expressions just by using cameras. Two promising technologies have been recently developed and freely released looking for brings emotional intelligence to our systems: the AffectivaSDK and the IntelReal Sense Camera. These tools allow capturing information of eight different emotions, five facial expressions and fourteen hand gestures. This bachelor project embraces the design and development of a software toolkit, the EmoCam Panel which allows to access all of the data from these affective tools and stream it to video games developed in Unity3D, thus enabling game developers and researchers include emotional intelligence in their applications. A proof of concept was developed using a custom-made endless runner video game in which three different adaptive rules were defined for modifying game events through emotional responses. Moreover, the EmoCam panel can be connected with the tools developed in the NeurorehabLab for serious games, for health investigation, thus extending the capabilities of these tools via including emotion sensing technologies.

Authors
Diogo Freitas; John Edison Muñoz; Sergi Bermúdez i Badia
Date
2017
Source

## Citation

@techreport{freitas2017,
author = {Freitas, D and Mu{\~n}oz, JE and i Badia, S Bermudez},
month = {6},
title = {EmoCam: Capturing emotions using non-invasive technologies},
year = {2017}
}