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Comparison of Angle and Size Features with Deep Learning for Emotion Recognition

: Dunau, Patrick; Huber, Marco; Beyerer, Jürgen


Vera-Rodriguez, R.:
Progress in pattern recognition, image analysis, computer vision, and applications. 23rd Iberoamerican congress, CIARP 2018 : Madrid, Spain, November 19-22, 2018; Proceedings
Cham: Springer International Publishing, 2019 (Lecture Notes in Computer Science 11401)
ISBN: 978-3-030-13468-6 (Print)
ISBN: 978-3-030-13469-3 (Online)
ISBN: 3-030-13468-7
Iberoamerican Congress on Pattern Recognition (CIARP) <23, 2018, Madrid>
Fraunhofer IPA ()
Fraunhofer IOSB ()
Bildauswertung; deep learning; Klassifikation; Mensch-Maschine-Interaktion

The 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.