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Image browsing with PCA-assisted user-interaction

: Keller, I.; Meiers, T.; Ellerbrock, T.; Sikora, T.


IEEE Computer Society, Technical Comittee on Pattern Analysis and Machine Intelligence:
IEEE Workshop on Content-Based Access of Image and Video Libraries, CBAIVL 2001. Proceedings : 14 December 2001, Kauai, Hawaii
Los Alamitos, Calif.: IEEE Computer Society, 2001
ISBN: 0-7695-1354-9
ISBN: 0-7695-1355-7
ISBN: 0-7695-1356-5
Workshop on Content Based Access of Image and Video Libraries (CBAIVL) <2001, Kauai/Hawaii>
Fraunhofer HHI ()
data visualisation; eigenvalues and eigenfunctions; image retrieval; principal component analysis; real-time systems; relevance feedback; search engines; user interfaces; image browsing; pca-assisted user-interaction; sophisticated search engines; browsing tool; user search intention; real time systems; visual human system; spatial information; virtual 3d space; image features; very high-dimensional mpeg-7 descriptors; visual presentation; high-dimensional descriptor components; covariance-matrix; eigenvalues; eigenspaces; relevance feedback methods

User interfaces for sophisticated search engines must offer users quick and easy access to the objects to be visualized. We present a browsing tool which arranges images with respect to the user search intention in a continuous and intuitive manner in real time. Since the capacity of the visual human system is higher for spatial information, we prefer a virtual 3D space for the visualization. Because our image features are described in terms of very high-dimensional MPEG-7 descriptors, we have to reduce them to only three dimensions for visual presentation. The dimension reduction is realized by an appropriate weighting of the high-dimensional descriptor components corresponding to a modification of the covariance-matrix used for principal component analysis (PCA). In addition, this modification allows us to overcome a problem arising from equally sized eigenvalues and provides varying eigenspaces nearly continuously. The technique introduced is a general approach, which can be combined with other relevance feedback methods.