Picture management using person retrieval for consumer image collections

In the last years the huge evolution of digital photography lead to an increasing interest in developing algorithms for indexing and classifying collections of digital images. This paper presents an automatic system for organizing and browsing through consumer digital image collections using the persons in the images as patterns. In order to implement such an automatic system we have to detect and classify the people in the images according to their similarities. For this we employ algorithms for face detection, face recognition and additional methods to cope with large variations that are usually present in consumer images. These additional methods includes using more than one type of classifiers for face recognition and also using additional information about the person characteristics extracted from other region than the face. This additional information will be more robust to factors that influence the accuracy of classical face recognition systems when working with consumer images. The proposed system was tested using a typical consumer image collection and practical applications using the system are presented in the end.