Reference-based indexing for metric spaces with costly distance measures
The VLDB Journal — The International Journal on Very Large Data Bases
The MPEG-7 Multimedia Database System (MPEG-7 MMDB)
Journal of Systems and Software
Multimedia Retrieval Algorithmics
SOFSEM '07 Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science
Optimal Pivots to Minimize the Index Size for Metric Access Methods
SISAP '09 Proceedings of the 2009 Second International Workshop on Similarity Search and Applications
Selecting vantage objects for similarity indexing
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Indexing dense nested metric spaces for efficient similarity search
PSI'09 Proceedings of the 7th international Andrei Ershov Memorial conference on Perspectives of Systems Informatics
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To make similarity searching in multimedia databases practical, indexing has become a necessity. Vantage indexing is an indexing technique which maps a dissimilarity space onto a vector space such that each object is represented by a vector of dissimilarities to a small set of m reference objects, the vantage objects. Querying takes place within this vector space, reducing the number of distance calculations to m. The retrieval performance of a system based on this technique can be improved significantly through a proper choice of vantage objects. We propose a new technique for selecting vantage objects and present experimental results based on data sets of different modality.