Imperial College London
Alternate

ProfessorKrystianMikolajczyk

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor in Computer Vision and Machine Learning
 
 
 
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Contact

 

+44 (0)20 7594 6220k.mikolajczyk

 
 
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Location

 

Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Schubert:2013:10.1007/978-3-642-40246-3_11,
author = {Schubert, F and Mikolajczyk, K},
doi = {10.1007/978-3-642-40246-3_11},
pages = {83--90},
title = {Benchmarking GPU-based phase correlation for homography-based registration of aerial imagery},
url = {http://dx.doi.org/10.1007/978-3-642-40246-3_11},
year = {2013}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Many multi-image fusion applications require fast registration methods in order to allow real-time processing. Although the most popular approaches, local-feature-based methods, have proven efficient enough for registering image pairs at real-time, some applications like multi-frame background subtraction, super-resolution or high-dynamic-range imaging benefit from even faster algorithms. A common trend to speed up registration is to implement the algorithms on graphic cards (GPUs). However not all algorithms are specially suited for massive parallelization via GPUs. In this paper we evaluate the speed of a well-known global registration method, i.e. phase correlation, for computing 8-DOF homographies. We propose a benchmark to compare a CPU- and GPU-based implementation using different systems and a dataset of aerial imagery. We demonstrate that phase correlation benefits from GPU-based implementations much more than local methods, significantly increasing the processing speed. © 2013 Springer-Verlag.
AU  - Schubert,F
AU  - Mikolajczyk,K
DO  - 10.1007/978-3-642-40246-3_11
EP  - 90
PY  - 2013///
SN  - 0302-9743
SP  - 83
TI  - Benchmarking GPU-based phase correlation for homography-based registration of aerial imagery
UR  - http://dx.doi.org/10.1007/978-3-642-40246-3_11
ER  -
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