Dunau, PatrickPatrickDunauHuber, MarcoMarcoHuberBeyerer, JürgenJürgenBeyerer2022-03-142022-03-142019https://publica.fraunhofer.de/handle/publica/40440810.1007/978-3-030-13469-3_70The robust recognition of a person's emotion from images is an important task in human-machine interaction. This task can be considered a classification problem, for which a plethora of methods exists. In this paper, the emotion recognition performance of two fundamentally different approaches is compared: classification based on hand-crafted features against deep learning. This comparison is conducted by means of well-established datasets and highlights the benefits and drawbacks of each approach.enBildauswertungdeep learningKlassifikationMensch-Maschine-Interaktion004670conference paper