In this paper, a system for automatic albuming of consumer photographs is described, and its specific core components of event segmentation and screening of low quality images are discussed. A novel event segmentation algorithm was created to automatically cluster pictures into events and sub-events for albuming, based on date/time metadata information as well as color content of the pictures. A new quality-screening algorithm is developed based on object quality measures, to detect problematic images due to underexposure, low contrast, and camera defocus or movement. Performance testing of these algorithms was conducted using a database of real consumer photos and showed that these functions provide a useful firstcut album layout for typical rolls of consumer pictures. A first version of the automatic albuming application software was tested through a consumer trial in the United States from August to December 1999.
Alexander C. Loui, Andreas E. Savakis