Fast feature matching based on r-nearest k-means searching

Fast feature matching based on r-nearest k-means searching

Feature matching has been frequently applied in computer vision and pattern recognition. In this paper, the authors propose a fast feature matching algorithm for vector-based feature. Their algorithm searches r-nearest neighborhood clusters for the query point after a k-means clustering, which shows...

Full description

Bibliographic Details
Main Authors: Ke Wang, Ningyu Zhu, Yao Cheng, Ruifeng Li, Tianxiang Zhou, Xuexiong Long
Format: Article
Language:English
Published: Wiley 2018-12-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
image matching
search problems
pattern clustering
feature extraction
trees (mathematics)
computer vision
pattern recognition
fast feature matching algorithm
vector-based feature
algorithm searches
nearest neighbourhood clusters
complex tree
nearest searching strategy
NN
searching speed
matching rule
wrong matches
searching points
priority search km-tree
random kd-tree
linear search
CFI algorithm
Online Access:https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1041

Internet

https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1041

Similar Items