Abstract
Emotions analysis and recognition by the smartphones with front cameras is a relatively new concept. In this paper we present an algorithm that uses a low resolution 3D sensor for facial expression recognition. The 3D head pose as well as 3D location of the fiducial points are determined using Face Tracking SDK. Tens of the features are automatically selected from a pool determined by all possible line segments between such facial landmarks. We compared correctly classified ratios using features selected by AdaBoost, Lasso and histogram-based algorithms. We compared the classification accuracies obtained both on 3D maps and RGB images. Our results justify the feasibility of low accuracy 3D sensing devices for facial emotion recognition.
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Malawski, F., Kwolek, B., Sako, S. (2014). Using Kinect for Facial Expression Recognition under Varying Poses and Illumination. In: Ślȩzak, D., Schaefer, G., Vuong, S.T., Kim, YS. (eds) Active Media Technology. AMT 2014. Lecture Notes in Computer Science, vol 8610. Springer, Cham. https://doi.org/10.1007/978-3-319-09912-5_33
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DOI: https://doi.org/10.1007/978-3-319-09912-5_33
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