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A comparative analysis of machine learning algorithms in detecting deceptive behaviour in humans using thermal images

Publication Type : Conference Proceedings

Publisher : Proceedings of the 2019 IEEE International Conference on Communication and Signal Processing, ICCSP 2019

Source : Proceedings of the 2019 IEEE International Conference on Communication and Signal Processing, ICCSP 2019. Institute of Electrical and Electronics Engineers Inc., Melmaruvathur; India, pp. 310-314, 2019

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065590610&doi=10.1109%2fICCSP.2019.8697911&partnerID=40&md5=6f0e978858f5878eb1741294986814be

ISBN : 9781538675953

Keywords : Comparative analysis, Comparative studies, Data mining, Deception, Decision trees, Infrared imaging, K-nearest neighbors, Lawrencium, Learning algorithms, Logistic regressions, Machine learning, Modern technologies, Motion compensation, Nearest neighbor search, Pre-orbital region, Regression analysis, Thermal imaging technology

Campus : Amritapuri

School : Department of Computer Science and Engineering, School of Engineering

Center : Computer Vision and Robotics

Department : Computer Science

Verified : No

Year : 2019

Abstract : Various researches are going on to identify the deceptive behaviour in humans by means of modern technology. The traditional and long term method used for detection is the polygraph technology, however it is not considered reliable. Impressive research works have been made in the last few decades to detect the deceptional behaviour in humans in a most promising way. Thermal imaging technology which is a rising trend can be applied to figure out the stress levels in humans by assessing the heat radiated from facial region. In this approach we record the difference in temperature in the pre-orbital region to discriminate between a truth teller and a liar. This paper aims at a comparative study of machine learning algorithms on a facial thermal image data set. By using the three algorithms K-Nearest Neighbor, Logistic Regression and Decision Tree we attempted to create a method that can detect lies. We arrived at a solution that gave 90% accuracy for K-Nearest Neighbor, Logistic Regression each and 85% accuracy for Decision Tree. © 2019 IEEE.

Cite this Research Publication : A. Ravindran, G. Krishna, G., Sagara,, and Sarath S., “A comparative analysis of machine learning algorithms in detecting deceptive behaviour in humans using thermal images”, Proceedings of the 2019 IEEE International Conference on Communication and Signal Processing, ICCSP 2019. Institute of Electrical and Electronics Engineers Inc., Melmaruvathur; India, pp. 310-314, 2019

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