Seungyup Paek, Carl L. Sable, Vasileios Hatzivassiloglou, Alejandro Jaimes, Barry H. Schiffman, Shih-Fu Chang, Kathleen R. McKeown. Integration of Visual and Text Based Approaches for the Content Labeling and Classification of Photographs. In ACM SIGIR'99 Workshop on Multimedia Indexing and Retrieval, Berkeley, CA, August 1999.
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Annotating photographs automatically with content descriptions facilitates organization, storage, and search over visual information. We present an integrated approach for scene classi cation that combines image-based and text-based approaches. On the text side, we use the text accompanying an image in a novel TF*IDF vector-based approach to classi cation. On the image side, we present a novel OF*IIF (object frequency) vector-based approach to classi cation. Objects are de ned by clustering of segmented regions of training images. The image based OF*IIF approach is synergistic with the text based TF*IDF approach. By integrating the TF*IDF approach and the OF*IIF approach, we achieved a classi cation accuracy of 86%. This is an improvement of approximately 12% over existing image classi ers, an im- provement of approximately 3% over the TF*IDF image classi er based on textual information, and an improvement of approximately 4% over the OF*IIF image classi er based on visual information
Seungyup Paek 
Alejandro Jaimes
Shih-Fu Chang
@InProceedings{dvmmPub78,
Author = {Paek, Seungyup and L. Sable, Carl and Hatzivassiloglou, Vasileios and Jaimes, Alejandro and H. Schiffman, Barry and Chang, Shih-Fu and R. McKeown, Kathleen},
Title = {Integration of Visual and Text Based Approaches for the Content Labeling and Classification of Photographs},
BookTitle = {ACM SIGIR'99 Workshop on Multimedia Indexing and Retrieval},
Address = {Berkeley, CA},
Month = {August},
Year = {1999}
}
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