OPTIMIZED ACTION UNITS FEATURES FOR EFFICIENT DESIGN OF DECEPTION DETECTION SYSTEM

Abstract

Deception detection is becoming an interesting filed in different areas related to security, criminal investigation, law enforcement and terrorism detection. Recently non-verbal features have become essential features for deception detection process. One of the most important kind of these features is facial expression. The importance of these expressions come from the idea that Human face contain different expressions each of which is directly related to a certain state. In this research paper, facial expressions' data are collected for 102 participants (25 women and 77 men) as video clips. There are 504 clips for lie response and 384 for truth response (total 888 video clips). Facial expressions in a form of Action Units (AUs) are extracted for each frame with video clip. The AUs are encoded based on Facial Action Coding System (FACS) which are 18 AUs. These are: AU 1, 2, 4, 5, 6, 7, 9, 10, 12, 14, 15, 17, 20, 23, 25, 26, 28 and 45. Based on the collected data, only six AUs are the most effective and have a direct impact on the discrimination process between liar and truth teller. These AUs are AU 6, 7, 10, 12, 14 and 28

Keywords

• deception detection, facial expressions, appearance features, geometry features, face detection, landmark detection and FACS