Classifier Fusion for Robust ICAO Compliant Face Analysis

Biometrics is a huge and very fast growing domain of methods for uniquely recognizing humans based on one or more intrinsic physical or behavioral traits with applications in many different areas, e.g., surveillance, person verification and identification. The International Civil Aviation Organization (ICAO) provides a number of specifications to prepare automated recognition from travel document photos. The goal of these specifications is to increase security in civil aviation on the basis of standardized biometric data. Due to this international standard, there is a high demand for automatically checking face images to assist civil service employees in decision-making. In this work, we present a face normalization and analysis system implementing several parts of the ICAO specification. Our key contribution of this analysis is the fusion of different established classifiers to boost performance of the overall system. Our results show the superior checking quality on facial images due to utilizing classifier fusion compared to a single classifier decision.