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174
An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions
 ACMSIAM SYMPOSIUM ON DISCRETE ALGORITHMS
, 1994
"... Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any po ..."
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Cited by 984 (32 self)
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Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any
Nearestneighbor searching and metric space dimensions
 In NearestNeighbor Methods for Learning and Vision: Theory and Practice
, 2006
"... Given a set S of n sites (points), and a distance measure d, the nearest neighbor searching problem is to build a data structure so that given a query point q, the site nearest to q can be found quickly. This paper gives a data structure for this problem; the data structure is built using the distan ..."
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Cited by 107 (0 self)
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Given a set S of n sites (points), and a distance measure d, the nearest neighbor searching problem is to build a data structure so that given a query point q, the site nearest to q can be found quickly. This paper gives a data structure for this problem; the data structure is built using
Nearest neighbor queries in metric spaces
 Discrete Comput. Geom
, 1997
"... Given a set S of n sites (points), and a distance measure d, the nearest neighbor searching problem is to build a data structure so that given a query point q, the site nearest to q can be found quickly. This paper gives data structures for this problem when the sites and queries are in a metric spa ..."
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Cited by 111 (1 self)
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Given a set S of n sites (points), and a distance measure d, the nearest neighbor searching problem is to build a data structure so that given a query point q, the site nearest to q can be found quickly. This paper gives data structures for this problem when the sites and queries are in a metric
An investigation of practical approximate nearest neighbor algorithms
, 2004
"... This paper concerns approximate nearest neighbor searching algorithms, which have become increasingly important, especially in high dimensional perception areas such as computer vision, with dozens of publications in recent years. Much of this enthusiasm is due to a successful new approximate neares ..."
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Cited by 115 (4 self)
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This paper concerns approximate nearest neighbor searching algorithms, which have become increasingly important, especially in high dimensional perception areas such as computer vision, with dozens of publications in recent years. Much of this enthusiasm is due to a successful new approximate
Accelerating nearest neighbor search on manycore systems
, 2011
"... Abstract—We develop methods for accelerating metric similarity search that are effective on modern hardware. Our algorithms factor into easily parallelizable components, making them simple to deploy and efficient on multicore CPUs and GPUs. Despite the simple structure of our algorithms, their searc ..."
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Cited by 14 (0 self)
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Abstract—We develop methods for accelerating metric similarity search that are effective on modern hardware. Our algorithms factor into easily parallelizable components, making them simple to deploy and efficient on multicore CPUs and GPUs. Despite the simple structure of our algorithms
PatchMatch: A Randomized Correspondence Algorithm for . . .
, 2009
"... This paper presents interactive image editing tools using a new randomized algorithm for quickly finding approximate nearestneighbor matches between image patches. Previous research in graphics and vision has leveraged such nearestneighbor searches to provide a variety of highlevel digital image ..."
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Cited by 243 (9 self)
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This paper presents interactive image editing tools using a new randomized algorithm for quickly finding approximate nearestneighbor matches between image patches. Previous research in graphics and vision has leveraged such nearestneighbor searches to provide a variety of highlevel digital image
Fractal Image Compression via Nearest Neighbor Search
 Conf. Proc. NATO ASI Fractal Image Encoding and Analysis
, 1996
"... In fractal image compression the encoding step is computationally expensive. A large number of sequential searches through a list of domains (portions of the image) are carried out while trying to find best matches for other image portions called ranges. Our theory developed here shows that this bas ..."
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Cited by 22 (7 self)
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that this basic procedure of fractal image compression is equivalent to multidimensional nearest neighbor search in a space of feature vectors. This result is useful for accelerating the encoding procedure in fractal image compression. The traditional sequential search takes linear time whereas the nearest
Reverse spatial and textual k nearest neighbor search
 In SIGMOD Conference
, 2011
"... ABSTRACT Geographic objects associated with descriptive texts are becoming prevalent. This gives prominence to spatial keyword queries that take into account both the locations and textual descriptions of content. Specifically, the relevance of an object to a query is measured by spatialtextual si ..."
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Cited by 24 (2 self)
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textual similarity that is based on both spatial proximity and textual similarity. In this paper, we define Reverse Spatial Textual k Nearest Neighbor (RSTk NN) query, i.e., finding objects that take the query object as one of their k most spatialtextual similar objects. Existing works on reverse kNN queries focus
A graphics hardware accelerated algorithm for nearest neighbor search
 Computational Science – ICCS 2006, volume 3994 of LNCS
, 2006
"... Abstract. We present a GPU algorithm for the nearest neighbor search, an important database problem. The search is completely performed using the GPU: No further postprocessing using the CPU is needed. Our experimental results, using large synthetic and realworld data sets, showed that our GPU alg ..."
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Cited by 13 (0 self)
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Abstract. We present a GPU algorithm for the nearest neighbor search, an important database problem. The search is completely performed using the GPU: No further postprocessing using the CPU is needed. Our experimental results, using large synthetic and realworld data sets, showed that our GPU
GPUAccelerated nearest neighbor search for 3d registration
 In Proc. of the 7th Int. Conf. on Computer Vision Systems: Computer Vision Systems
, 2009
"... Abstract. Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for realtime capability. The basic problem is in rapidly processing a huge amount of data, which is often addressed by means of highly sophistica ..."
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Cited by 10 (0 self)
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Abstract. Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for realtime capability. The basic problem is in rapidly processing a huge amount of data, which is often addressed by means of highly
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