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Improved Feature Extraction Technique for Handling Occlusion in Automatic Facial Expression Recognition
2019
Zenodo
The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their
doi:10.5281/zenodo.2643966
fatcat:anbcpqaz2fdkbp2ovzuneabywa