Multi-frame decision level fusion for face classification based on a photon-counting linear discriminant analysis
Seokwon Yeom · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Face classification in an uncontrolled setting has wide applications in security and surveillance systems. Multiple frames are often available for this purpose captured by multiple sensors or a single sensor generating video clips. Data fusion technique for face classification has an advantage in that a considerable amount of information can be used to achieve high recognition performance. This paper investigates the efficacy of multi-frame decision level fusion for face classification based on a photon-counting linear discriminant analysis, which realizes Fisher's criterion without dimensionality reduction. Decision level fusion comprises two stages: score validation and score combination. During score validation, candidate symbols (classes) are selected by a screening process. During score combination, the candidate scores are combined in order to make a final decision. In the experiments, a facial image database is employed to show the preliminary results of the proposed technique.