Hybrid Machine Learning Model for Lie-Detection

Abstract

A technique for recognizing a person from his photograph is facial recognition. Due to its extensive range of applications in several fields, it has drawn the attention of numerous researchers in the field of computer vision in recent years (Cyber security, crime cases, and biometrics). This technology's operation is based on the extraction of features from an input picture using methods like PCA, ICA, LDA etc. After comparing them with others from another image to verify or assert an individual's identification. Via this work, we applied amalgamation of CNN and SVM techniques to two face datasets that will be split into two groups in a machine learning-based methodology. We assessed different machine learning-based lie detectors using our amassed dataset. Our findings demonstrate that combined CNN with SVM task achieved accuracy up to 58%.