Nearest Neighbor Search on Multimedia Indexing Structures

Nearest Neighbor Search on Multimedia Indexing Structures Multimedia databases get larger and larger in our days, and this trend is expected to continue in the future. There are various aspects that affect the demand for efficient database techniques to manage the flood of multimedia data, namely the increasing number of objects, the increasing complexity of objects, and the emergence of new query types. Whereas traditional indexing structures cope with large numbers of simple objects, complex multimedia objects require more sophisticated indexing techniques. In the tutorial, we discuss characteristics of multimedia data and multimedia queries including similarity range queries and k-nearest neighbor queries. The main focus is on efficient processing of k-nearest neighbor queries in various settings and includes direct k-NN search on indexes, multi-step k-NN query processing for complex distance functions and methods for high-dimensional spaces. 

• Type: Conference
• Year: 2004
• Where: CVDB
• Authors: Thomas Seidl
• Keywords: Computer Vision, CVDB 2004, Indexing Structures, K-nearest Neighbor Queries, Multimedia