In recent years, digital cameras are becoming very commonplace and
users need tools to manage large personal photo collections. In a typical
scenario, a user acquires a certain number of pictures and then
transfers this new photo sequence to his PC. Thus, before being added
to the whole personal photo collection, it would be desirable that this
new photo sequence is processed and organized. For example, users
may be interested in using (i.e., browsing, saving, printing and so on) a
subset of stored data according to some particular picture properties.
For these reasons, automatic techniques for content-based description
of personal photos are needed. Tools enabling an incremental
organization of the photo album should take advantage from the particular
properties of digital library. Indeed, personal photo collections
show peculiar characteristics as compared to generic image collections,
namely, a relatively small number of different individuals can be detected
across the whole collection and, generally, it is possible to group
the photos based on specific attributes. In such a scenario, the user
is mainly interested in who is in the picture and where and when the
picture was shot. Considering Who, where and when as the fundamental
aspects of photo information, in this thesis it will be given a
detailed description of novel approaches for content-based image retrieval.
Novel image analysis techniques will be presented, focusing
in particular on face information. Then, two novel frameworks for
personal photo organization will be shown