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 meta data information as well as color content of the pictures. A new quality-screening is developed based on object quality 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 first-cut 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.
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
IEEE International Conference on Multimedia and Expo 2 (2000) 1125-1128
RIT – Main Campus