Genetic Programming-Evolved Spatio-Temporal Descriptor for Human Action Recognition
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{BMVC.26.18,
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author = "Li Liu and Ling Shao and Peter Rockett",
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title = "Genetic Programming-Evolved Spatio-Temporal Descriptor
for Human Action Recognition",
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year = "2012",
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booktitle = "Proceedings of the British Machine Vision Conference,
BMVC 2012",
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editors = "Richard Bowden and John P. Collomosse and Krystian
Mikolajczyk",
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pages = "18.1--18.12",
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address = "Surrey, UK",
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month = sep # " 3-7",
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publisher = "BMVA Press",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-901725-46-4",
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bibdate = "2013-04-24",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/bmvc/bmvc2012.html#LiuSR12",
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URL = "http://www.bmva.org/bmvc/2012/BMVC/paper018/paper018.pdf",
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URL = "http://www.bmva.org/bmvc/2012/BMVC/paper018/index.html",
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DOI = "doi:10.5244/C.26.18",
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size = "12 pages",
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abstract = "The potential value of human action recognition has
led to it becoming one of the most active research
subjects in computer vision. In this paper, we propose
a novel method to automatically generate low-level
spatio-temporal descriptors showing good performance,
for high-level human-action recognition tasks. We
address this as an optimisation problem using genetic
programming (GP), an evolutionary method, which
produces the descriptor by combining a set of primitive
3D operators. As far as we are aware, this is the first
report of using GP for evolving spatio-temporal
descriptors for action recognition. In our evolutionary
architecture, the average cross-validation
classification error calculated using the
support-vector machine (SVM) classifier is used as the
GP fitness function. We run GP on a mixed dataset
combining the KTH and the Weizmann datasets to obtain a
promising feature-descriptor solution for action
recognition. To demonstrate generalisable, the best
descriptor generated so far by GP has also been tested
on the IXMAS dataset leading to better accuracies
compared with some previous hand-crafted descriptors",
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notes = "Also known as \cite{conf/bmvc/LiuSR12}",
- }
Genetic Programming entries for
Li Liu
Ling Shao
Peter I Rockett
Citations