UDC 004.422.635.3, DOI: 10.2298/CSIS1001139H

MFI-Tree: An Effective Multi-feature Index Structure for Weighted Query Application

Yunfeng He1 and Junqing Yu1

  1. School of Computer Science & Technology, Huazhong University of Science & Technology
    430074 Wuhan, China
    yjqing@hust.edu.cn

Abstract

Multi-Feature Index Tree (MFI-Tree) a new indexing structure, is proposed to index multiple high-dimensional features of video data for video retrieval through example. MFI-Tree employs tree structure which is beneficial for the browsing application, and retrieves the last level cluster nodes in retrieval application to improve the performance. Aggressive Decided Distance for kNN (ADD-kNN) search algorithm is designed because it can effectively reduce the distance to prune the search space. Experimental results demonstrate that the MFI-Tree and ADD-kNN algorithm have the advantages over sequential scan in performance.

Key words

Multi-Feature Index Tree; KNN; Aggressive Decided Distance for kNN; Video Retrieval

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS1001139H

Publication information

Volume 7, Issue 1 (February 2010)
Advances in Computer Animation and Digital Entertainment
Year of Publication: 2010
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

He, Y., Yu, J.: MFI-Tree: An Effective Multi-feature Index Structure for Weighted Query Application. Computer Science and Information Systems, Vol. 7, No. 1. (2010)