2020
DOI: 10.3390/s20174847
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Feature Selection on 2D and 3D Geometric Features to Improve Facial Expression Recognition

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 … Show more

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Cited by 15 publications
(6 citation statements)
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“…As the very start in 3D FER, the data description is the most fundamental and crucial. A simple but widely used way of the data description in the literature on 3D FER is the vectorization (See, e.g., [24,25,31,37,38,45,46,49,55,56]). However, the main drawback that vectorization suffers is the loss of the internal structure information of the data samples in which potential or inherent sparsity may hidden, and hence the dimensionality curse comes along by dismissing these favorable structural properties.…”
Section: Introductionmentioning
confidence: 99%
“…As the very start in 3D FER, the data description is the most fundamental and crucial. A simple but widely used way of the data description in the literature on 3D FER is the vectorization (See, e.g., [24,25,31,37,38,45,46,49,55,56]). However, the main drawback that vectorization suffers is the loss of the internal structure information of the data samples in which potential or inherent sparsity may hidden, and hence the dimensionality curse comes along by dismissing these favorable structural properties.…”
Section: Introductionmentioning
confidence: 99%
“…Geometric-based methods are to obtain the feature vector representing the facial expression by taking into account the positions and shapes of the turning points (eye, mouth, eyebrow, nose) on the face [14]. There are many geometric-based studies in the FER field [15][16][17][18][19][20][21].…”
Section: Introductionmentioning
confidence: 99%
“… Feature extraction: Feature construction and/or selection is usually based on the coordinates obtained from (a), and either an appearance or a geometric approach can be used. The former employs the texture of the skin and facial wrinkles, whereas the latter employs the shape, i.e., distances and angles of facial components [ 12 ]. Classification: The last step concerns the classification of different emotions or expressions.…”
Section: Introductionmentioning
confidence: 99%