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A Survey based on Machine Learning Approaches for Detection of Human Behavioural Lie using physiological sensors and Face Recognition System

Bishan Lal Thakur1 , Divyansh Thakur2 , Payal Pandey3

Section:Survey Paper, Product Type: Journal Paper
Volume-6 , Issue-11 , Page no. 797-806, Nov-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i11.797806

Online published on Nov 30, 2018

Copyright © Bishan Lal Thakur, Divyansh Thakur, Payal Pandey . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Bishan Lal Thakur, Divyansh Thakur, Payal Pandey, “A Survey based on Machine Learning Approaches for Detection of Human Behavioural Lie using physiological sensors and Face Recognition System,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.797-806, 2018.

MLA Style Citation: Bishan Lal Thakur, Divyansh Thakur, Payal Pandey "A Survey based on Machine Learning Approaches for Detection of Human Behavioural Lie using physiological sensors and Face Recognition System." International Journal of Computer Sciences and Engineering 6.11 (2018): 797-806.

APA Style Citation: Bishan Lal Thakur, Divyansh Thakur, Payal Pandey, (2018). A Survey based on Machine Learning Approaches for Detection of Human Behavioural Lie using physiological sensors and Face Recognition System. International Journal of Computer Sciences and Engineering, 6(11), 797-806.

BibTex Style Citation:
@article{Thakur_2018,
author = {Bishan Lal Thakur, Divyansh Thakur, Payal Pandey},
title = {A Survey based on Machine Learning Approaches for Detection of Human Behavioural Lie using physiological sensors and Face Recognition System},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2018},
volume = {6},
Issue = {11},
month = {11},
year = {2018},
issn = {2347-2693},
pages = {797-806},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3246},
doi = {https://doi.org/10.26438/ijcse/v6i11.797806}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i11.797806}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3246
TI - A Survey based on Machine Learning Approaches for Detection of Human Behavioural Lie using physiological sensors and Face Recognition System
T2 - International Journal of Computer Sciences and Engineering
AU - Bishan Lal Thakur, Divyansh Thakur, Payal Pandey
PY - 2018
DA - 2018/11/30
PB - IJCSE, Indore, INDIA
SP - 797-806
IS - 11
VL - 6
SN - 2347-2693
ER -

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Abstract

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.

Key-Words / Index Term

Machine learning techniques, Physiological Sensors, Face Recognition, Emotion Recognition, Lie Detection

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