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Continuous Nearest Neighbor Search

by Yufei Tao, Dimitris Papadias, Qiongmao Shen , 2002
"... A continuous nearest neighbor query retrieves the nearest neighbor (NN) of every point on a line segment (e.g., "find all my nearest gas stations during my route from point s to point e"). The result contains a set of <point, interval> tuples, such that point is the NN of all po ..."
Abstract - Cited by 160 (10 self) - Add to MetaCart
points in the corresponding interval. Existing methods for continuous nearest neighbor search are based on the repetitive application of simple NN algorithms, which incurs significant overhead. In this paper we propose techniques that solve the problem by performing a single query for the whole

Nearest Neighbor Search Methods

by Surbhi Chaudhry, Xiabing Xu, Dr. Nancy Amato , 2008
"... The motion planning problem consists of finding a valid path for a robot (movable object) from a start configuration to a goal configuration without colliding with any obstacle. Probabilistic road map (PRM) methods use randomization to construct a graph (road map) of collision-free paths that attemp ..."
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improve the performance of path planners. The brute force method of nearest neighbor search has a complexity of O(n2).This increases the running time and hence the cost. The cost of nearest-neighbor calls is one of the bottlenecks in the performance of sampling-based motion planning algorithms. Therefore

Nearest Neighbor Search in Multidimensional Spaces

by Panayiotis Tsaparas , 1999
"... The Nearest Neighbor Search problem is defined as follows: given a set P of n points, preprocess the points so as to efficiently answer queries that require finding the closest point in P to a query point q. If we are willing to settle for a point that is almost as close as the nearest neighbor, t ..."
Abstract - Cited by 11 (0 self) - Add to MetaCart
The Nearest Neighbor Search problem is defined as follows: given a set P of n points, preprocess the points so as to efficiently answer queries that require finding the closest point in P to a query point q. If we are willing to settle for a point that is almost as close as the nearest neighbor

Product quantization for nearest neighbor search

by Hervé Jégou, Matthijs Douze, Cordelia Schmid , 2010
"... This paper introduces a product quantization based approach for approximate nearest neighbor search. The idea is to decomposes the space into a Cartesian product of low dimensional subspaces and to quantize each subspace separately. A vector is represented by a short code composed of its subspace q ..."
Abstract - Cited by 222 (31 self) - Add to MetaCart
This paper introduces a product quantization based approach for approximate nearest neighbor search. The idea is to decomposes the space into a Cartesian product of low dimensional subspaces and to quantize each subspace separately. A vector is represented by a short code composed of its subspace

Nearest neighbor search in . . .

by Alexandr Andoni , 2010
"... ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Abstract not found

Clustering-based Nearest Neighbor Searching

by Ping Ling, Xiangsheng Rong, Yongquan Dong
"... Abstract—This paper proposes a Clustering-based Nearest Neighbor Search algorithm (CNNS) for high dimensional data. Different from existing approaches that are based on rigid-grid partition to develop data access structure, CNNS creates indexing structures according to data inherent distribution, wi ..."
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Abstract—This paper proposes a Clustering-based Nearest Neighbor Search algorithm (CNNS) for high dimensional data. Different from existing approaches that are based on rigid-grid partition to develop data access structure, CNNS creates indexing structures according to data inherent distribution

Privacy Preserving Nearest Neighbor Search

by Mark Shaneck , 2006
"... Data mining is frequently obstructed by privacy concerns. In many cases data is distributed, and bringing the data together in one place for analysis is not possible due to privacy laws (e.g. HIPAA) or policies. Privacy preserving data mining techniques have been developed to address this issue by p ..."
Abstract - Cited by 24 (1 self) - Add to MetaCart
by providing mechanisms to mine the data while giving certain privacy guarantees. In this work we address the issue of privacy preserving nearest neighbor search, which forms the kernel of many data mining applications. To this end, we present a novel algorithm based on secure multiparty computation primitives

Nearest-Neighbor Searching Under Uncertainty

by Pankaj K. Agarwal, Alon Efrat, Wuzhou Zhang, et al. , 2012
"... Nearest-neighbor queries, which ask for returning the nearest neighbor of a query point in a set of points, are important and widely studied in many fields because of a wide range of applications. In many of these applications, such as sensor databases, location based services, face recognition, and ..."
Abstract - Cited by 17 (7 self) - Add to MetaCart
Nearest-neighbor queries, which ask for returning the nearest neighbor of a query point in a set of points, are important and widely studied in many fields because of a wide range of applications. In many of these applications, such as sensor databases, location based services, face recognition

Nearest-Neighbor Searching Under Uncertainty

by Wuzhou Zhang , 2012
"... Nearest-neighbor queries, which ask for returning the nearest neighbor of a query point in a set of points, are important and widely studied in many fields because of a wide range of applications. In many of these applications, such as sensor databases, location based services, face recognition, and ..."
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Nearest-neighbor queries, which ask for returning the nearest neighbor of a query point in a set of points, are important and widely studied in many fields because of a wide range of applications. In many of these applications, such as sensor databases, location based services, face recognition

Nearest Neighbor Search for Relevance Feedback

by Jelena Tesic, B.S. Manjunath - In Proc. CVPR , 2003
"... We introduce the problem of repetitive nearest neighbor search in relevance feedback and propose an efficient search scheme for high dimensional feature spaces. Relevance feedback learning is a popular scheme used in content based image and video retrieval to support high-level concept queries. This ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
We introduce the problem of repetitive nearest neighbor search in relevance feedback and propose an efficient search scheme for high dimensional feature spaces. Relevance feedback learning is a popular scheme used in content based image and video retrieval to support high-level concept queries
Results 1 - 10 of 1,656