Deception/Truthful Prediction Based on Facial Feature and Machine Learning Analysis

Abstract

The Automatic Deception detection refers to the investigative practices used to determine whether person is telling you Truth or lie. Automatic deception detection has been studied extensively as it can be useful in many real-life scenarios in health, justice, and security systems. Many psychological studies have been reported for deception detection.  Polygraph testing is a current trending technique to detect deception, but it requires human intervention and training.  In recent times, many machine learning based approaches have been applied to detect deceptions. Various modalities like Thermal Imaging, Brain Activity Mapping, Acoustic analysis, eye tracking. Facial Micro expression processing and linguistic analyses are used to detect deception. Machine learning techniques based on facial feature analysis look like a promising path for automatic deception detection. It also works without human intervention. So, it may give better results because it does not affect race or ethnicity. Moreover, one can do covert operation to find deceit using facial video recording. Covert Operation may capture the real personality of deceptive persons. By making combination of various facial features like Facial Emotion, Facial Micro Expressions and Eye blink rate, pupil size, Facial Action Units we can get better accuracy in Deception Detection.