A Survey based on Machine Learning Approaches for Detection of Human Behavioural Lie using physiological sensors and Face Recognition System
DOI:
https://doi.org/10.26438/ijcse/v6i11.797806Keywords:
Machine learning techniques, Physiological Sensors, Face Recognition, Emotion Recognition, Lie DetectionAbstract
At present there is a huge need of system which uses both physiological and facial data to detect human behavioral lie, thus this survey is based on getting insight for developing a machine learning based technique using facial and physiological data for detection of human behavior. The purpose of this survey is to identify various physiological sensors and their parameters along with sensing data, also to know whether physiological signals are robust and can be controlled by human being or not. It also reviews about various machine learning techniques for face recognition system and presented the most effective face recognition system in our survey. By getting significant understanding of physiological data and facial data with their classification rate it becomes possible to deduce a machine learning based algorithm using facial and physiological data for detection of human behavioral lie. This survey compiled the work done by various author to provide the precise information about the machine learning techniques, physiological sensors, face recognition system for human behavioral lie.
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