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- W2592439416 abstract "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, the new encoding methods significantly improve the recognition accuracy and the robustness of analysis for a variety of applications." @default.
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- W2592439416 date "2017-02-05" @default.
- W2592439416 modified "2023-09-27" @default.
- W2592439416 title "Robust Features Face." @default.
- W2592439416 hasPublicationYear "2017" @default.
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