scispace - formally typeset
Proceedings ArticleDOI

Feature-based retrieval of similar shapes

TLDR
A shape similarity-based retrieval method for image databases that supports a variety of queries that is flexible with respect to the choice of feature and definition of similarity and is implementable using existing multidimensional point access methods.
Abstract
A shape similarity-based retrieval method for image databases that supports a variety of queries is proposed It is flexible with respect to the choice of feature and definition of similarity and is implementable using existing multidimensional point access methods A prototype system that handles the problems of distortion and occlusion is described Experiments with one specific point access method (PAM) are presented >

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Book ChapterDOI

When Is ''Nearest Neighbor'' Meaningful?

TL;DR: The effect of dimensionality on the "nearest neighbor" problem is explored, and it is shown that under a broad set of conditions, as dimensionality increases, the Distance to the nearest data point approaches the distance to the farthest data point.
Journal Article

When is nearest neighbor meaningful

TL;DR: In this article, the authors explore the effect of dimensionality on the nearest neighbor problem and show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance of the farthest data point.
Book ChapterDOI

The X-tree: an index structure for high-dimensional data

TL;DR: A new organization of the directory is introduced which uses a split algorithm minimizing overlap and additionally utilizes the concept of supernodes to keep the directory as hierarchical as possible, and at the same time to avoid splits in the directory that would result in high overlap.
Journal ArticleDOI

Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases

TL;DR: An overview of the current state of the art in querying multimedia databases is provided, describing the index structures and algorithms for an efficient query processing in high-dimensional spaces.
Proceedings ArticleDOI

The pyramid-technique: towards breaking the curse of dimensionality

TL;DR: The results of experiments demonstrate that the Pyramid-Technique outperforms the X-tree and the Hilbert R-tree by a factor of up to 14 (number of page accesses) and up to 2500 (total elapsed time) for range queries.
References
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Proceedings ArticleDOI

R-trees: a dynamic index structure for spatial searching

TL;DR: A dynamic index structure called an R-tree is described which meets this need, and algorithms for searching and updating it are given and it is concluded that it is useful for current database systems in spatial applications.
Proceedings ArticleDOI

The R*-tree: an efficient and robust access method for points and rectangles

TL;DR: The R*-tree is designed which incorporates a combined optimization of area, margin and overlap of each enclosing rectangle in the directory which clearly outperforms the existing R-tree variants.
Journal ArticleDOI

The Grid File: An Adaptable, Symmetric Multikey File Structure

TL;DR: This work discusses in detail the design decisions that led to the grid file, present simulation results of its behavior, and compare it to other multikey access file structures.
Proceedings ArticleDOI

The K-D-B-tree: a search structure for large multidimensional dynamic indexes

TL;DR: The K-D-B-tree as mentioned in this paper is a data structure that combines the properties of K-d-tree and B-tree. But it does not support range queries.
Proceedings ArticleDOI

Geometric Hashing: A General And Efficient Model-based Recognition Scheme

TL;DR: A general method for model-based object recognition in occluded scenes is presented based on geometric hashing, which stands out for its efficiency and applications both in 3-D and 2-D.
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