A fast nearest neighbor search algorithm by nonlinear embedding
We propose an efficient algorithm to find the exact nearest neighbor based on the Euclidean
distance for large-scale computer vision problems. We embed data points nonlinearly onto a …
distance for large-scale computer vision problems. We embed data points nonlinearly onto a …
Fast algorithm for nearest neighbor search based on a lower bound tree
This paper presents a novel algorithm for fast nearest neighbor search. At the preprocessing
stage, the proposed algorithm constructs a lower bound tree by agglomeratively clustering …
stage, the proposed algorithm constructs a lower bound tree by agglomeratively clustering …
Towards meaningful high-dimensional nearest neighbor search by human-computer interaction
CC Aggarwal - Proceedings 18th International Conference on …, 2002 - ieeexplore.ieee.org
Nearest neighbor search is an important and widely used problem in a number of important
application domains. In many of these domains, the dimensionality of the data …
application domains. In many of these domains, the dimensionality of the data …
Fast k nearest neighbor search using GPU
Statistical measures coming from information theory represent interesting bases for image
and video processing tasks such as image retrieval and video object tracking. For example …
and video processing tasks such as image retrieval and video object tracking. For example …
A simple algorithm for nearest neighbor search in high dimensions
SA Nene, SK Nayar - IEEE Transactions on pattern analysis …, 1997 - ieeexplore.ieee.org
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 …
recognition. Unfortunately, the complexity of most existing search algorithms, such as kd tree …
Clustering billions of images with large scale nearest neighbor search
T Liu, C Rosenberg, HA Rowley - 2007 IEEE workshop on …, 2007 - ieeexplore.ieee.org
The proliferation of the Web and digital photography have made large scale image
collections containing billions of images a reality. Image collections on this scale make …
collections containing billions of images a reality. Image collections on this scale make …
A CUDA-based parallel implementation of K-nearest neighbor algorithm
S Liang, Y Liu, C Wang, L Jian - 2009 International Conference …, 2009 - ieeexplore.ieee.org
Recent developments in Graphics Processing Units (GPUs) have enabled inexpensive high
performance computing for general-purpose applications. Due to GPU's tremendous …
performance computing for general-purpose applications. Due to GPU's tremendous …
Scalable nearest neighbor algorithms for high dimensional data
For many computer vision and machine learning problems, large training sets are key for
good performance. However, the most computationally expensive part of many computer …
good performance. However, the most computationally expensive part of many computer …
What is the most efficient way to select nearest neighbor candidates for fast approximate nearest neighbor search?
Approximate nearest neighbor search (ANNS) is a basic and important technique used in
many tasks such as object recognition. It involves two processes: selecting nearest neighbor …
many tasks such as object recognition. It involves two processes: selecting nearest neighbor …
Nearest-neighbor search algorithms on non-Euclidean manifolds for computer vision applications
P Turaga, R Chellappa - Proceedings of the seventh Indian conference …, 2010 - dl.acm.org
Nearest-neighbor searching is a crucial component in many computer vision applications
such as face recognition, object recognition, texture classification, and activity recognition …
such as face recognition, object recognition, texture classification, and activity recognition …