TY  - JOUR
T1  - Design and Implementation of Deception Detection System
Based on Reliable Facial Expression
AU - H. Thannoon, Harith AU - H. Ali, Wissam AU - A. Hashim, Ivan 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 15
SP  - 5002
EP  - 5011
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.5002.5011
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.5002.5011
KW  - Movement
KW  -facial muscle
KW  -database
KW  -video clips
KW  -spotting liars
KW  -validate
AB  - <p>Human face is a wealthy source of information which provides reliable cues to deception. The
Deceptive Detection Systems (DDSs) through the identification of facial expression are non-invasive, mobile
and cost effective. In this study, the DDS is designed depending on Facial Action Coding System (FACS) to
extract the facial features. The main idea of this FACS is coded the facial muscles movements using Action
Units (AUs). Each AU represented the movement of certain facial muscle. The proposed system discriminates
lying subjects from the innocent one based on presence or absent the facial AUs. Eight AUs are used as
potential indicators for deception that incorporated into a single facial behavior pattern vector. Database that
used to validate the proposed system are collected from 43 subjects (20 males, 23 females) most of them
between ages 18-25. The number of video clips that obtained from collected database after editing was 400
video clips. Virtual Generalizing Random Access Memory Weightless Neural Network (VG-RAM WNN)
classifier is used to make decision in last stage of DDS. The proposed DDS was tested three times, accuracy
84, 85 and 90% of spotting liars are achieved when using both genders, only female and only male participants
respectively. The VG-RAM classifier was built by FPGA Model using Xilinx system generator and implemented
on Spartan-3A 700 A Kit.</p>
ER  -