MA Abschlussvortrag, Shashank Rao, Ort: O27/545, Datum: 30.10.2018, Zeit: 10:30 Uhr

The intent behind this thesis is to do a qualitative analysis of current infrastructure
and techniques for emotion detection and create models that combine the discussed
modalities for emotion detection (e.g., driver inattention, facial expressions,
physiological signals and driving contexts) in order to improve the accuracy in detection
of negative emotions and negative states (frustration/anger/disgust, panic/fear
and boredom/fatigue/inattentiveness). The models obtained provide us with further
information that can improve the quality of predictions as emotion detection still remains
as a very fuzzy and a difficult task. This will facilitate our aim to improve driver
safety for future cars through its interfaces.