Person Identification From Audio and Visual Aesthetics

Abstract

In recent years, the trend that allowed for person identification based on behavior rather than physical traits to emerge as a growing research domain. Its application spans areas such as online education, e-commerce, e-communication, human-computer interaction, robotics, and biometric security. The expression of opinions is an example of online behavior, that is commonly shared through the liking of images or music. A person's aesthetic preference involves using a person's sense of fondness to experienced stimulus. This thesis examines for the first time aesthetic preference as a biometric trait. It then establishes the efficacy of a combined multi-modal approach to person identification using aesthetic preference. The potency of this approach is tested on a proprietary dataset.