Analysis of Embeddings Learned by End-to-End Machine Learning Eye Movement-driven Biometrics Pipeline

arXiv:2402.16399v1 Announce Type: cross
Abstract: This paper expands on the foundational concept of temporal persistence in biometric systems, specifically focusing on the domain of eye movement biometrics facilitated by machine learning. Unlike previous studies that primarily focused on developing biometric authentication systems, our research delves into the embeddings learned by these systems, particularly examining their temporal persistence, reliability, and biometric efficacy in response to varying input data. Utilizing two publicly available eye-movement datasets, we employed the state-of-the-art Eye Know You …

analysis arxiv authentication biometric biometrics concept cs.cr cs.cv domain end end-to-end machine machine learning persistence pipeline research studies systems temporal