A Dimensionality Reduction Method for Efficient Search of High-Dimensional Databases
Summary :
In this paper, we present a novel approach for efficient search of high-dimensional databases, such as video shots. The idea is to map feature vectors from the high-dimensional feature space into a point in a low-dimensional distance space. Then, a spatial access method, such as an R-tree, is used to cluster these points based on their distances in the low-dimensional space. Our mapping method, called topological mapping, guarantees no false dismissals in the result of a query. However, the result of a query might contain some false alarms. Hence, two refinement steps are performed to remove these false alarms. Comparative experiments on a database of video shots show the superior efficiency of the topological mapping method over other known methods.
- Publication
- IEICE TRANSACTIONS on Information Vol.E86-D No.6 pp.1032-1041
- Publication Date
- 2003/06/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Databases
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Zaher AGHBARI, Kunihiko KANEKO, Akifumi MAKINOUCHI, "A Dimensionality Reduction Method for Efficient Search of High-Dimensional Databases" in IEICE TRANSACTIONS on Information,
vol. E86-D, no. 6, pp. 1032-1041, June 2003, doi: .
Abstract: In this paper, we present a novel approach for efficient search of high-dimensional databases, such as video shots. The idea is to map feature vectors from the high-dimensional feature space into a point in a low-dimensional distance space. Then, a spatial access method, such as an R-tree, is used to cluster these points based on their distances in the low-dimensional space. Our mapping method, called topological mapping, guarantees no false dismissals in the result of a query. However, the result of a query might contain some false alarms. Hence, two refinement steps are performed to remove these false alarms. Comparative experiments on a database of video shots show the superior efficiency of the topological mapping method over other known methods.
URL: https://global.ieice.org/en_transactions/information/10.1587/e86-d_6_1032/_p
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@ARTICLE{e86-d_6_1032,
author={Zaher AGHBARI, Kunihiko KANEKO, Akifumi MAKINOUCHI, },
journal={IEICE TRANSACTIONS on Information},
title={A Dimensionality Reduction Method for Efficient Search of High-Dimensional Databases},
year={2003},
volume={E86-D},
number={6},
pages={1032-1041},
abstract={In this paper, we present a novel approach for efficient search of high-dimensional databases, such as video shots. The idea is to map feature vectors from the high-dimensional feature space into a point in a low-dimensional distance space. Then, a spatial access method, such as an R-tree, is used to cluster these points based on their distances in the low-dimensional space. Our mapping method, called topological mapping, guarantees no false dismissals in the result of a query. However, the result of a query might contain some false alarms. Hence, two refinement steps are performed to remove these false alarms. Comparative experiments on a database of video shots show the superior efficiency of the topological mapping method over other known methods.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - A Dimensionality Reduction Method for Efficient Search of High-Dimensional Databases
T2 - IEICE TRANSACTIONS on Information
SP - 1032
EP - 1041
AU - Zaher AGHBARI
AU - Kunihiko KANEKO
AU - Akifumi MAKINOUCHI
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E86-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2003
AB - In this paper, we present a novel approach for efficient search of high-dimensional databases, such as video shots. The idea is to map feature vectors from the high-dimensional feature space into a point in a low-dimensional distance space. Then, a spatial access method, such as an R-tree, is used to cluster these points based on their distances in the low-dimensional space. Our mapping method, called topological mapping, guarantees no false dismissals in the result of a query. However, the result of a query might contain some false alarms. Hence, two refinement steps are performed to remove these false alarms. Comparative experiments on a database of video shots show the superior efficiency of the topological mapping method over other known methods.
ER -
English
