Genetic programming for improving image descriptors generated using the scale-invariant feature transform
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{conf/ivcnz/HindmarshAZ12,
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author = "Samuel Hindmarsh and Peter Andreae and Mengjie Zhang",
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title = "Genetic programming for improving image descriptors
generated using the scale-invariant feature transform",
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booktitle = "Image and Vision Computing New Zealand, IVCNZ, 2012",
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year = "2012",
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editor = "Brendan McCane and Steven Mills and Jeremiah D. Deng",
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pages = "85--90",
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address = "Dunedin, New Zealand",
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month = nov # " 26-28",
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publisher = "ACM",
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keywords = "genetic algorithms, genetic programming, SIFT, object
recognition",
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isbn13 = "978-1-4503-1473-2",
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URL = "http://dl.acm.org/citation.cfm?id=2425836",
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DOI = "doi:10.1145/2425836.2425855",
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acmid = "2425855",
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bibdate = "2013-01-15",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/ivcnz/ivcnz2012.html#HindmarshAZ12",
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size = "6 pages",
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abstract = "Object recognition is an important task in the
computer vision field as it has many applications,
including optical character recognition and facial
recognition. However, many existing methods have
demonstrated relatively poor performance in all but the
most simple cases. Scale-invariant feature transform
(SIFT) features attempt to alleviate issues surrounding
complex examples involving variances in scale, rotation
and illumination, but suffer, potentially, from the way
the algorithm describes the key points it detects in
images. Genetic programming (GP) is used for the first
time in an attempt to find the optimal way of
describing the image keypoints extracted by the SIFT
algorithm. Training and testing results show that the
fittest program from a GP search can improve on the
standard SIFT descriptors after only a few generations
of a small population. While early results may not yet
show major improvements over standard SIFT features,
they do open the door for further research and
experimentation.",
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notes = "IVCNZ",
- }
Genetic Programming entries for
Samuel Hindmarsh
Peter Andreae
Mengjie Zhang
Citations