Facial Expression Recognition using Computer Vision and Machine Learning: A Path to Deception Detection

Thesis Type: Postgraduate

Institution Of The Thesis: Cranfield University, School of Aerospace, Transport and Manufacturing, Computational and Software Techniques in Engineering, England

Thesis Supervisor: Zeeshan A. Rana

Approval Date: 2019

Thesis Language: English

Abstract:

Facial expressions are global emotional signs that make interpersonal communication cohesive. At the same moment, the modifications in facial expressions in emotional psychology are regarded as the most significant clues. Analysis of facial expression has a wider variety of applications in fields such as human behaviour analysis, communication between humans, and communication between human and computer. While beings have no trouble in acknowledging and understanding facial expressions, machines are having a difficult issue. But knowing natural urges by machine has become an indispensable problem, particularly with developments in human-computer interaction. In addition, facial expression analysis and identification have pervaded different fields such as defence, sociology, education, engineering, and augmented reality. For these purposes, the rapid analysis of facial expressions and the correct identification of facial expressions according to the evaluated facial expressions hold a critical position in various apps for several software programs. The impacts of facial expressions on the identification of deception have been studied in this research.