Robust features for facial action recognition [article]

Nadav Israel, Lior Wolf, Ran Barzilay, Gal Shoval
2017 arXiv   pre-print
Automatic recognition of facial gestures is becoming increasingly important as real world AI agents become a reality. In this paper, we present an automated system that recognizes facial gestures by capturing local changes and encoding the motion into a histogram of frequencies. We evaluate the proposed method by demonstrating its effectiveness on spontaneous face action benchmarks: the FEEDTUM dataset, the Pain dataset and the HMDB51 dataset. The results show that, compared to known methods,
more » ... e new encoding methods significantly improve the recognition accuracy and the robustness of analysis for a variety of applications.
arXiv:1702.01426v2 fatcat:slqsnysu2bbvjk3izkwp5avafi