Nearest-neighbor searching is a crucial component in many computer vision applications
such as face recognition, object recognition, texture classification, and activity recognition …

We can define the nearest neighbor search (NSS) problem in the following way: given a set
of points P= p1, p2,..., pn in a metric space X, these points must be preprocessed in such a …

The nearest neighbor search is an essential operation for many computer vision, data
mining, and machine learning problems. Since it is so widely used, the nearest neighbor …

The problem of finding the closest point in high-dimensional spaces is common in pattern
recognition. Unfortunately, the complexity of most existing search algorithms, such as kd tree …

Nearest neighbor search is a computational primitive whose efficiency is paramount to many
applications. As such, the literature recently blossomed with many works focusing on …

The approximating and eliminating search algorithm (AESA) is probably the technique
requiring the fewest distance computations for nearest-neighbour searching in general …

Nearest neighbor search (NNS) in high dimensional space is a fundamental and essential
operation in applications from many domains, such as machine learning, databases …

A novel approach for k-nearest neighbor (k-NN) searching with Euclidean metric is
described. It is well known that many sophisticated algorithms cannot beat the brute-force …

In this paper, we present a fast and versatile algorithm which can rapidly perform a variety of
nearest neighbor searches. Efficiency improvement is achieved by utilizing the distance …

Proximity searching can be formulated as an optimization problem, being the goal function
to find the object minimizing the distance to a given query by traversing a graph with a …