Consumers often make more than one photograph of the same scene, creating
non-identical duplicates and near duplicates. In Kodaks consumer
photography database, on average, 19% of the images, per roll, fall into
this category. Automatic detection of duplicates, therefore, is extremely
useful in applications that help users organize their image collections.
We introduce the challenging problem of non-identical duplicate image
detection in consumer photography, describe STELLA (a novel interactive
personal image collection organization system), and give an overview of
our novel framework for detecting duplicate and near duplicate consumer
photographs and news videos.
Prof. Shih-Fu Chang
A. Jaimes, S.-F. Chang and A. C. Loui, Duplicate Detection in Consumer
Photography and News Video, ACM Multimedia 2002, Juan Les Pines, France,
A. Jaimes, Conceptual Structures and Computational Methods for Indexing
and Organization of Visual Information, Doctoral Dissertation, Graduate
School of Arts and Sciences, Columbia University, 2003 (Advisor: Prof.
Object/Scene Detection by Learning Random Attributed Relational Graph
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Last updated: June 12, 2002.