Imperial College London

DrKrystianMikolajczyk

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Reader in Computer Vision
 
 
 
//

Contact

 

+44 (0)20 7594 6220k.mikolajczyk

 
 
//

Location

 

Electrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@inproceedings{Miksik:2012,
author = {Miksik, O and Mikolajczyk, K},
pages = {2681--2684},
publisher = {IEEE},
title = {Evaluation of local detectors and descriptors for fast feature matching},
year = {2012}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - Local feature detectors and descriptors are widely used in many computer vision applications and various methods have been proposed during the past decade. There have been a number of evaluations focused on various aspects of local features, matching accuracy in particular, however there has been no comparisons considering the accuracy and speed trade-offs of recent extractors such as BRIEF, BRISK, ORB, MRRID, MROGH and LIOP. This paper provides a performance evaluation of recent feature detectors and compares their matching precision and speed in randomized kd-trees setup as well as an evaluation of binary descriptors with efficient computation of Hamming distance. © 2012 ICPR Org Committee.
AU - Miksik,O
AU - Mikolajczyk,K
EP - 2684
PB - IEEE
PY - 2012///
SN - 1051-4651
SP - 2681
TI - Evaluation of local detectors and descriptors for fast feature matching
ER -