Abstract
An essential aspect in the interaction between people and computers is the recognition of facial expressions. A key issue in this process is to select relevant features to classify facial expressions accurately. This study examines the selection of optimal geometric features to classify six basic facial expressions: happiness, sadness, surprise, fear, anger, and disgust. Inspired by the Facial Action Coding System (FACS) and the Moving Picture Experts Group 4th standard (MPEG-4), an initial set of 89 features was proposed. These features are normalized distances and angles in 2D and 3D computed from 22 facial landmarks. To select a minimum set of features with the maximum classification accuracy, two selection methods and four classifiers were tested. The first selection method, principal component analysis (PCA), obtained 39 features. The second selection method, a genetic algorithm (GA), obtained 47 features. The experiments ran on the Bosphorus and UIVBFED data sets with 86.62% and 93.92% median accuracy, respectively. Our main finding is that the reduced feature set obtained by the GA is the smallest in comparison with other methods of comparable accuracy. This has implications in reducing the time of recognition.
Highlights
People use cognitive mechanisms to recognize emotions during the communication process.One cognitive mechanism is to understand the non-verbal human behavior
This has been investigated for decades since 1872 with the study of Darwin, which involves a cognitive analysis of facial expressions [1]
We proposed a cognitive system for emotion recognition, where the main difference is observed in the selection of features
Summary
People use cognitive mechanisms to recognize emotions during the communication process. One cognitive mechanism is to understand the non-verbal human behavior. This has been investigated for decades since 1872 with the study of Darwin, which involves a cognitive analysis of facial expressions [1]. In 1978, Suwa et al presented the first attempt to automatically analyze facial expressions [2]. Ekman and Friesen proposed a standard called Facial Action. This standard is composed of 44 facial Action Units (AUs) describing all facial movements. Ekman proposed the six basic universal emotions: happiness, sadness, surprise, fear, anger, and disgust [2,3]
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