DocumentCode
357112
Title
Automatic image event segmentation and quality screening for albuming applications
Author
Loui, Alexander C. ; Savakis, Andreas E.
Author_Institution
Imaging Sci. & Technol. Lab., Eastman Kodak Co., Rochester, NY, USA
Volume
2
fYear
2000
fDate
2000
Firstpage
1125
Abstract
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 rested through a consumer trial in the United States from August to December 1999
Keywords
image colour analysis; image segmentation; meta data; multimedia databases; visual databases; automatic albuming system; automatic image event segmentation; automatic picture clustering; color content; consumer photographs; date/time metadata information; events; first-cut album layout; object quality; performance testing; photo database; problematic image detection; quality screening; sub-events; Application software; Automatic testing; Clustering algorithms; Digital cameras; Image databases; Image segmentation; Internet; Laboratories; Object detection; Software testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Expo, 2000. ICME 2000. 2000 IEEE International Conference on
Conference_Location
New York, NY
Print_ISBN
0-7803-6536-4
Type
conf
DOI
10.1109/ICME.2000.871558
Filename
871558
Link To Document