Kolloquium Dienstag, 18.02.14 10:00 Uhr, WE5/5.013
Johannes Folger (MA AI): Classification of Facial Expressions of Pain from Video Streams
The main concern of this thesis was the development and evaluation of an approach for classifying pain from video streams. In contrast to the analysis of individual images, videos provide temporal information that can improve the classification of facial expressions. The presented approach considered such kind of information by extracting data from temporal frames of different sizes. The method was evaluated by classifying pain, disgust, and neutral expressions within video sequences of four different subjects. As this work is considered to be a pilot study, three individual classifiers were trained and tested only in a person-dependent manner. Results showed that all classifiers obtained mean accuracy rates above chance. Additionally, no classifier could achieve outstanding performances and the size of the temporal frames seems to have no influence on the performance results. One reason for this could be the number of attributes considered for machine learning.