SPIESR
2004
13 years 5 months ago
2004
This paper presents an overview of our recent work on managing image and video data. The first half of the paper describes a representation for the semantic spatial layout of vide...
CCCG
2006
13 years 5 months ago
2006
For a given point set in Euclidean space we consider the problem of finding (approximate) nearest neighbors of a query point but restricting only to points that lie within a fixed...
PODS
1989
ACM
13 years 8 months ago
1989
ACM
In this paper we propose the use of fractals and especially the Hilbert curve, in order to design good distance-preserving mappings. Such mappings improve the performance of secon...
SSD
2001
Springer
13 years 9 months ago
2001
Springer
In this paper we introduce the notion of constrained nearest neighbor queries (CNN) and propose a series of methods to answer them. This class of queries can be thought of as neare...
ICDT
2001
ACM
13 years 9 months ago
2001
ACM
Abstract. Nearest-neighbor queries in high-dimensional space are of high importance in various applications, especially in content-based indexing of multimedia data. For an optimiz...
DAWAK
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. In this paper, we present a new approach to indexing multidimensional data that is particularly suitable for the efficient incremental processing of nearest neighbor quer...
STOC
2002
ACM
14 years 4 months ago
2002
ACM
Given a set S of n points in IRd , a (t, )-approximate Voronoi diagram (AVD) is a partition of space into constant complexity cells, where each cell c is associated with t represe...
ICDE
2001
IEEE
14 years 5 months ago
2001
IEEE
In this paper, we develop a general framework for approximate nearest neighbor queries. We categorize the current approaches for nearest neighbor query processing based on either ...
ICDE
2002
IEEE
14 years 5 months ago
2002
IEEE
We investigate techniques for analysis and retrieval of object trajectories in a two or three dimensional space. Such kind of data usually contain a great amount of noise, that ma...