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2019
Conference Paper
Titel
Reduced feature set for emotion recognition based on angle and size information
Abstract
The correct interpretation of facial emotions is important for many applications like psychology or human-machine interaction. In this paper, a novel set of features for emotion classification from images is introduced. Based on landmark points extracted from the face, angles between point-connecting lines and size information of mouth and eyes are extracted. Experiments compare the quality and reliability of the feature set to landmark-based features and facial action unit based features.