In this paper we present a novel approach to personal photo album management allowing the end user to efficiently access the collection without any need for tedious manual annotation or indexing of the photos. The proposed work exploits methods and technology from the field of computer vision and pattern recognition for
face detection, face representation and image annotation to automatically create description of images useful for
content-based searching and retrieval. In fact, even if most of the used techniques are not reliable enough to address the general problem of content-based image retrieval, we show that, in a limited domain such as the one of personal photo album, it is possible to obtain results that improve the browsing capabilities of current photo album management systems. In particular, starting from the observation that most personal photos depict a usually small number of people in a relatively small number of different context (indoor, outdoor, beach, mountain, city, etc...) we propose the use of automatic techniques to index images based on who is present in the scene and on the context where the picture was taken. Experiments on a personal photo collection of about a thousand images proved that relatively simple content-based techniques lead to surprisingly good results in term of easyness of user access to the data.