Deep Parameter Optimisation for Face Detection Using the Viola-Jones Algorithm in OpenCV
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Bruce:2016:SSBSE,
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author = "Bobby R. Bruce and Jonathan M. Aitken and
Justyna Petke",
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title = "Deep Parameter Optimisation for Face Detection Using
the {Viola-Jones} Algorithm in {OpenCV}",
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booktitle = "Proceedings of the 8th International Symposium on
Search Based Software Engineering, SSBSE 2016",
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year = "2016",
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editor = "Federica Sarro and Kalyanmoy Deb",
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volume = "9962",
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series = "LNCS",
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pages = "238--243",
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address = "Raleigh, North Carolina, USA",
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month = "8-10 " # oct,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, genetic
improvement, SBSE, OpenCV, NSGA-II, Deep parameter
optimisation, Automated parameter tuning,
Multi-objective optimisation, GI",
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isbn13 = "978-3-319-47106-8",
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URL = "http://www.cs.ucl.ac.uk/staff/J.Petke/papers/Bruce_2016_SSBSE.pdf",
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DOI = "doi:10.1007/978-3-319-47106-8_18",
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code_url = "https://github.com/BobbyRBruce/DPT-OpenCV",
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size = "6 pages",
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abstract = "OpenCV is a commonly used computer vision library
containing a wide variety of algorithms for the AI
community. This paper uses deep parameter optimisation
to investigate improvements to face detection using the
Viola-Jones algorithm in OpenCV, allowing a trade-off
between execution time and classification accuracy. Our
results show that execution time can be decreased by 48
percent if a 1.80 percent classification inaccuracy is
permitted (compared to 1.04 percent classification
inaccuracy of the original, unmodified algorithm).
Further execution time savings are possible depending
on the degree of inaccuracy deemed acceptable by the
user.",
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notes = "See correction \cite{bruce:RN1707} Tarball of
repository is available
http://www.cs.ucl.ac.uk/staff/R.Bruce/dpt_opencv.tar.gz",
- }
Genetic Programming entries for
Bobby R Bruce
Jonathan M Aitken
Justyna Petke
Citations