Improved SOM search algorithm for high-dimensional data with application to face recognition across pose and illumination

摘要

In this paper we focus on dealing with large size databases. Such databases require the construction of suitable feature spaces to accommodate data. The paper presents a new search algorithm based on the self organizing map (SOM) avoids the high-cost of computation in such cases. The proposed SOM algorithm is combined with support vector machine (SVM) to form a new appearance based approach. The proposed approach is evaluated in face recognition experiments across variations in pose and illumination. A huge-size database is used to judge effectively the proposed approach. The results have compared with another reported approach based on light field theory using same huge database.