The face is an important source of information in multi-modal communication. Facial expressions are generated by contractions of facial muscles, which lead to subtle changes in the area of the eyelids, eye brows, nose, lips and skin texture, often revealed by wrinkles and bulges. To measure these subtle changes, Ekman et al. [5] developed the Facial Action Coding System (FACS). FACS is a human-observer-based system designed to detect subtle changes in facial features, and describes facial expressions by action units (AUs). We present a technique to automatically recognize lower facial Action Units, independently from one another. Even though we do not explicitly take into account AU combinations, thereby making the classification process harder, an average F1 score of 94.83% is achieved.
Gonzalez, I, Sahli, H & Verhelst, W 2010, Automatic Recognition of Lower Facial Action Units. in E Barakova, BD Ruyter & A Spink (eds), Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research. MB2010, ACM, pp. 1-4, Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet, Stockholm, Sweden, 21/09/09. <http://doi.acm.org/10.1145/1931344.1931352>
Gonzalez, I., Sahli, H., & Verhelst, W. (2010). Automatic Recognition of Lower Facial Action Units. In E. Barakova, B. D. Ruyter, & A. Spink (Eds.), Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research (pp. 1-4). (MB2010). ACM. http://doi.acm.org/10.1145/1931344.1931352
@inproceedings{4169c472f25845cf98b1d390f572a21f,
title = "Automatic Recognition of Lower Facial Action Units",
abstract = "The face is an important source of information in multi-modal communication. Facial expressions are generated by contractions of facial muscles, which lead to subtle changes in the area of the eyelids, eye brows, nose, lips and skin texture, often revealed by wrinkles and bulges. To measure these subtle changes, Ekman et al. [5] developed the Facial Action Coding System (FACS). FACS is a human-observer-based system designed to detect subtle changes in facial features, and describes facial expressions by action units (AUs). We present a technique to automatically recognize lower facial Action Units, independently from one another. Even though we do not explicitly take into account AU combinations, thereby making the classification process harder, an average F1 score of 94.83% is achieved.",
keywords = "facial action unit, AdaBoost, OVL, SVM",
author = "Isabel Gonzalez and Hichem Sahli and Werner Verhelst",
note = "Emilia Barakova, Boris de Ruyter, Andrew Spink; Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet ; Conference date: 21-09-2009 Through 25-09-2009",
year = "2010",
language = "English",
isbn = "978-1-60558-926-8",
series = "MB2010",
publisher = "ACM",
pages = "1--4",
editor = "Emilia Barakova and Ruyter, {Boris De} and Andrew Spink",
booktitle = "Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research",
}