Using an Individual Evolution Strategy for Stereovision
Created by W.Langdon from
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- @Article{louchet:2001:GPEM,
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author = "Jean Louchet",
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title = "Using an Individual Evolution Strategy for
Stereovision",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2001",
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volume = "2",
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number = "2",
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pages = "101--109",
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month = jun,
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keywords = "genetic algorithms, genetic programming, artificial
evolution, individual evolution strategy, flies,
computer vision, image processing, stereovision,
software engineering",
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ISSN = "1389-2576",
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broken = "http://ipsapp009.lwwonline.com/content/getfile/4723/5/2/fulltext.pdf",
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DOI = "doi:10.1023/A:1011544128842",
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abstract = "The fly algorithm is an individual evolution strategy
developed for parameter space exploration in computer
vision applications. In the application described, each
individual represents a geometrical point in the scene
and the population itself is used as a
three-dimensional model of the scene. A fitness
function containing all pixel-level calculations is
introduced to exploit simple optical and geometrical
properties and evaluate the relevance of each
individual as taking part to the scene representation.
Classical evolutionary operators (sharing, mutation,
crossover) are used. The combined individual approach
and low complexity fitness function allow fast
processing. Test results and extensions to real-time
image sequence processing, mobile objects tracking and
mobile robotics are presented.",
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notes = "Article ID: 335709",
- }
Genetic Programming entries for
Jean Louchet
Citations