Abstract
Many content-based multimedia data retrieval problems can be transformed into the near neighbor searching problem in multidimensional feature space. An efficient near neighbor searching algorithm is needed when developing a multimedia database system. In this paper, we propose an approach to efficiently solve the near neighbor searching problem. In this approach, along each dimension an index is constructed according to the values of feature points of multimedia objects. A user can pose a content-based query by specifying a multimedia query example and a similarity measure. The specified query example will be transformed into a query point in the multi-dimensional feature space. The possible result points in each dimension are then retrieved by searching the value of the query point in the corresponding dimension. The sets of the possible result points are merged one by one by removing the points which are not within the query radius. The resultant points and their distances from the query point form the answer of the query. To show the efficiency of our approach, a series of experiments are performed to compare with the related approaches.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
N. Bechmann, H.-P. Kriegel, R. Schneider, and B. Seeger, “The R*-tree: An efficient and robust access method for points and rectangles,” in Proc. of ACM SIGMOD Conf., 1990, pp. 322–331.
J.L. Bentley and J.H. Friedman, “Data structure for range searching,” ACM Computing Surveys, Vol. 11, No. 4, pp. 397–409, 1979.
J.L. Bentley, “Multidimensional binary search trees used for associative searching,” Communication of the ACM, Vol. 18, No. 9, pp. 509–517, 1975.
S. Brin, “Near neighbor search in large metric spaces,” in Proc. of the 21st International Conference on VLDB, 1995, pp. 574–584.
A.L.P. Chen, C.C. Liu, K.L. Lee, and C.C. Chen, “The design of a video database system,” in Proc. Real Time and Media Systems, 1995.
T.C. Chiueh, “Content-based image indexing,” in Proc. of 20th VLDB Conf., 1994, pp. 582–593.
T.C. Chou, A.L.P. Chen, and C.C. Liu, “Music databases: Indexing techniques and implementation,” in Proc. IEEE Intl. Workshop on Multimedia Data Base Management Systems, 1996.
N. Dimitrova and F. Golshani, “Motion recovery for video content classification,” ACMTrans. on Info. Sys., Vol. 13, No. 4, pp. 408–439, 1995.
C. Faloutsos and K.-I. Lin, “FastMap: A fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets,” in Proc. of ACM SIGMOD Conf., 1995.
R.A. Finkel and J.L. Bentley, “Quad trees: Adata structure for retrieval on composite keys,” Acta Informatica, Vol. 4, No. 1, pp. 1–9, 1974.
M. Freeston, “A general solution of the n-dimensional B-tree problem,” in Proc. of ACM SIGMOD Conf., 1995, pp. 80–91.
V.N. Gudivada and V.V. Raghavan, “Design and evaluation of algorithms for image retrieval by spatial similarity,” ACM Trans. on Info. Sys., Vol. 13, No. 2, pp. 115–144, 1995.
R.H. Guting, “An introduction to spatial database systems,” VLDB Journal, Vol. 3, No. 4, pp. 357–399, 1994.
A. Guttman,“R-trees: A dynamic index structure for spatial searching,” in Proc. of ACM SIGMOD Conf., 1984, pp. 47–75.
H.V. Jagadish, “A retrieval technique for similar shapes,” in Proc. of ACM SIGMOD Conf., 1991, pp. 208-217.
T.C.T. Kuo, Y.B. Lin, A.L.P. Chen, S.C. Chen, and C.Y. Ni, “Efficient shot change detection on compressed video data,” in Proc. IEEE Intl. Workshop on Multimedia Database Management Systems, 1996.
C.C. Liu and A.L.P. Chen, “Modeling and query processing of distributed multimedia databases,” in Proc. Real-Time and Media Systems, 1996.
C.C. Liu and A.L.P. Chen, “3D-List: A data structure for efficient video query processing,” IEEE Trans. on TKDE, to appear.
C.C. Liu and A.L.P. Chen, “Vega: A multimedia database system supporting content-based retrieval,” Information Science and Engineering, 1997.
C.C. Liu and A.L.P. Chen, “1D-List: A data structure for efficient approximate string matching,” NTHU Technical Report.
K.-I. Lin, H.V. Jagadish, and C. Faloutsos, “The TV-tree: An index structure for high-dimensional data,” VLDB Journal, Vol. 3, No. 4, pp. 519–544, 1994.
J. Nievrgelt, H. Hinterberger, and K.C. Sevcik, “The grid file: An adaptable, symmetric multikey file structure,” ACM Transactions on Database Systems, Vol. 9, No. 1, pp. 38–71, 1984.
N. Roussopoulos, S. Kelly, and F. Vincent, “Nearest neighbor query,” in Proc. of ACM SIGMOD Conf., 1995, pp. 71–79.
H. Samet, The Design and Analysis of Spatial Data Structures, Addison-Wesley, 1990.
T. Sellis, N. Roussopoulos, and C. Faloutsoso, “The R+ tree: A dynamic index for multi-dimensional objects,” in Proc. of the 13th International Conference on VLDB, 1987, pp. 507–518.
S.W. Smoliar and H.J. Zhang, “Content-based video indexing and retrieval,” IEEE Multimedia, Vol. 1, No. 2, pp. 62–72, 1994.
T.T.Y. Wai and A.L.P. Chen, “Retrieving videodata via motion tracks of content symbols,” in Proc. of ACM International Conference on Information and Knowledge Management (CIKM).
R. Weiss, A. Duda, and D.K. Gifford, “Composition and search with a video algebra,” IEEE Multimedia, Vol. 2, No. 1, pp. 12–25, 1995.
N. Peter Yianilos, “Data structures and algorithms for nearest neighbor search in general metric spaces,” in Proc. of the Forth Annual ACM-SIAM Symposium on Discrete Algorithm, 1993, pp. 311–321.
A. Yoshitaka, S. Kishida, M. Hirakawa and T. Ichikawa, “Knowledge-assisted content-based retrieval for multimedia databases,” IEEE Multimedia, Vol. 1, No. 4, pp. 12–21, 1994.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Liu, CC., Hsu, JL. & Chen, A.L. Efficient Near Neighbor Searching Using Multi-Indexes for Content-Based Multimedia Data Retrieval. Multimedia Tools and Applications 13, 235–254 (2001). https://doi.org/10.1023/A:1009601513674
Issue Date:
DOI: https://doi.org/10.1023/A:1009601513674