A Review of Automatic Lie Detection from Facial Features-Reference-Cited by-同舟云学术

A Review of Automatic Lie Detection from Facial Features

Published:2024-03 Issue:1 Volume:48 Page:93-136
ISSN:0191-5886
Container-title:Journal of Nonverbal Behavior
language:en
Short-container-title:J Nonverbal Behav

Author:

Delmas Hugues,Denault Vincent,Burgoon Judee K.,Dunbar Norah E.

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10919-024-00451-2.pdf

Reference173 articles.

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2. Avola, D., Cascio, M., Cinque, L., Fagioli, A., & Foresti, G. L. (2021). LieToMe: An ensemble approach for deception detection from facial cues. International Journal of Neural Systems, 31(2), 2050068. https://doi.org/10.1142/S0129065720500689

3. Bablani, A., Edla, D. R., Kupilli, V., & Dharavath, R. (2021). Lie detection using fuzzy ensemble approach with novel defuzzification method for classification of EEG signals. IEEE Transactions on Instrumentation and Measurement, 70, 1–13. https://doi.org/10.1109/TIM.2021.3082985

4. Baltrušaitis, T., Robinson, P., & Morency, L.-P. (2016). OpenFace: An open source facial behavior analysis toolkit. IEEE Winter Conference on Applications of Computer Vision (WACV), 2016, 1–10. https://doi.org/10.1109/WACV.2016.7477553

5. Barathi, C. S. (2016). Lie detection based on facial micro expression body language and speech analysis. International Journal of Engineering Research & Technology.

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