M. Ebner, и A. Zell. Evolutionary Image Analysis, Signal Processing and
Telecommunications: First European Workshop, EvoIASP'99
and EuroEcTel'99, том 1596 из LNCS, стр. 74--89. Goteborg, Sweden, Springer-Verlag, (28-29 May 1999)
Аннотация
Image processing is usually done by chaining a series
of well known image processing operators. Using
evolutionary methods this process may be automated. In
this paper we address the problem of evolving task
specific image processing operators. In general, the
quality of the operator depends on the task and the
current environment. Using genetic programming we
evolved an interest operator which is used to calculate
sparse optical flow. To evolve the interest operator we
define a series of criteria which need to be optimized.
The different criteria are combined into an overall
fitness function. Finally, we present experimental
results on the evolution of the interest operator.
%0 Conference Paper
%1 ebner:1999:etsio
%A Ebner, Marc
%A Zell, Andreas
%B Evolutionary Image Analysis, Signal Processing and
Telecommunications: First European Workshop, EvoIASP'99
and EuroEcTel'99
%C Goteborg, Sweden
%D 1999
%E Poli, Riccardo
%E Voigt, Hans-Michael
%E Cagnoni, Stefano
%E Corne, Dave
%E Smith, George D.
%E Fogarty, Terence C.
%I Springer-Verlag
%K algorithms, genetic programming
%P 74--89
%T Evolving a Task Specific Image Operator
%U http://citeseer.ist.psu.edu/392593.html
%V 1596
%X Image processing is usually done by chaining a series
of well known image processing operators. Using
evolutionary methods this process may be automated. In
this paper we address the problem of evolving task
specific image processing operators. In general, the
quality of the operator depends on the task and the
current environment. Using genetic programming we
evolved an interest operator which is used to calculate
sparse optical flow. To evolve the interest operator we
define a series of criteria which need to be optimized.
The different criteria are combined into an overall
fitness function. Finally, we present experimental
results on the evolution of the interest operator.
%@ 3-540-65837-8
@inproceedings{ebner:1999:etsio,
abstract = {Image processing is usually done by chaining a series
of well known image processing operators. Using
evolutionary methods this process may be automated. In
this paper we address the problem of evolving task
specific image processing operators. In general, the
quality of the operator depends on the task and the
current environment. Using genetic programming we
evolved an interest operator which is used to calculate
sparse optical flow. To evolve the interest operator we
define a series of criteria which need to be optimized.
The different criteria are combined into an overall
fitness function. Finally, we present experimental
results on the evolution of the interest operator.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {Goteborg, Sweden},
author = {Ebner, Marc and Zell, Andreas},
biburl = {https://www.bibsonomy.org/bibtex/216557aff848a0f97a9e5f258191ad3f3/brazovayeye},
booktitle = {Evolutionary Image Analysis, Signal Processing and
Telecommunications: First European Workshop, EvoIASP'99
and EuroEcTel'99},
editor = {Poli, Riccardo and Voigt, Hans-Michael and Cagnoni, Stefano and Corne, Dave and Smith, George D. and Fogarty, Terence C.},
interhash = {1365273e72a218bc32208f99e3ebfdda},
intrahash = {16557aff848a0f97a9e5f258191ad3f3},
isbn = {3-540-65837-8},
keywords = {algorithms, genetic programming},
month = {28-29 May},
notes = {EvoIASP99'99},
organisation = {EvoNet},
pages = {74--89},
publisher = {Springer-Verlag},
publisher_address = {Berlin},
series = {LNCS},
timestamp = {2008-06-19T17:39:02.000+0200},
title = {Evolving a Task Specific Image Operator},
url = {http://citeseer.ist.psu.edu/392593.html},
volume = 1596,
year = 1999
}