Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6941646 | Signal Processing: Image Communication | 2018 | 10 Pages |
Abstract
Recent methodologies for facial expression recognition have been proposed and have obtained good results in near-frontal view. However, these situations do not fairly represent in-the-wild challenges, where expressions are natural and the subject is free of its movement. This is reflected in the accuracy drop of facial expression methods obtained on recent databases. Two challenges (head pose variations and large displacements) in facial expression recognition are studied in this paper. Experiments are proposed in order to quantify the impact of free head movements using representative expression recognition approaches (LBP, LBP-TOP, HOOF). We propose an experimental protocol (SNaP-2DFe) that records, under controlled light, facial expressions with two cameras: one attached on the head and one placed in front of the subject. As in both cameras facial expressions are the same, differences in performances measured on each camera show the impact of head pose variations and large displacements on the underlying recognition approach.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
B. Allaert, J. Mennesson, I.M. Bilasco, C. Djeraba,