Title: Visual cues-based deception detection using two-class neural network

Authors: Sabu George; M.M. Manohara Pai; Radhika M. Pai; Samir Kumar Praharaj

Addresses: Department of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India ' Department of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India ' Department of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India ' Department of Psychiatry, Kasturba Medical College, Manipal Academy of Higher Education, Karnataka, India

Abstract: The deception detection technique which helps to analyse a person without his knowledge is convenient and effective than other methods of deception detection. In this paper, facial visual cues-based deception detection study is performed. In this study, an experiment was conducted with the participation of 62 subjects. Facial muscle variations of lie and truth responses of the subjects were recorded using a high speed camera and the corresponding action units (AUs) were trained and then tested for truth and lie prediction using two-class neural network. The prediction performance was analysed using five different sets each having 10%, 20% and 30% test samples.

Keywords: visual cues; AU analysis; deception detection; neural network.

DOI: 10.1504/IJCVR.2019.098796

International Journal of Computational Vision and Robotics, 2019 Vol.9 No.2, pp.132 - 151

Received: 01 May 2018
Accepted: 16 Jun 2018
Published online: 02 Apr 2019 *

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