A Review on Using Machine Learning to Conduct Facial Analysis in Real Time for Real-Time Profiling
Keywords:
Facial Micro-Expressions, Eye Blinks, Tool Kit, Facial Landmark, OpenCV, EAR, Machine Learning
Abstract
The micro facial expressions and eye blinks of the liar are analyzed by the lie detection system, which makes use of the Facial Landmark Detection System that is included in the OpenCV Tool Kit. While the suspect responds to a series of questions, the system will observe the motions of the facial muscles and the rate at which their eyes blink. The Eye-Opening Ratio is used to determine the eye-opening in each frame. An approach that makes use of human behaviors to identify deception has been proposed here. In order to assess whether a candidate is being dishonest during an interrogation and come up with a conclusion about them, the system will do face detection and an eye blink calculation. During an interrogation session, the interrogator can use this result to assist them in doing an analysis of the blink threshold value and locating the lie. In the future, developments could include thermal monitoring, which would involve collecting video of the suspect while they are answering questions during interrogation. This video would then be used in conjunction with face detection and eye blink rate to provide a more in-depth analysis of the suspect's dishonest behavior.
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Published
2023-02-23
How to Cite
T, S., Rajest, S. S., Regin, R., & R, S. (2023). A Review on Using Machine Learning to Conduct Facial Analysis in Real Time for Real-Time Profiling. International Journal of Human Computing Studies, 5(2), 18-37. https://doi.org/10.31149/ijhcs.v5i2.4032
