The Boru Data Crawler for Object Detection Tasks in Machine Vision

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Daniel Howard and Simon C. Roberts and Conor Ryan",
  title =        "The Boru Data Crawler for Object Detection Tasks in
                 Machine Vision",
  booktitle =    "Applications of Evolutionary Computing, Proceedings of
                 EvoWorkshops2002: EvoCOP, EvoIASP, EvoSTim/EvoPLAN",
  year =         "2002",
  editor =       "Stefano Cagnoni and Jens Gottlieb and Emma Hart and 
                 Martin Middendorf and G{"}unther Raidl",
  volume =       "2279",
  series =       "LNCS",
  pages =        "222--232",
  address =      "Kinsale, Ireland",
  publisher_address = "Berlin",
  month =        "3-4 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 computation, applications",
  ISBN =         "3-540-43432-1",
  DOI =          "doi:10.1007/3-540-46004-7_23",
  size =         "11 pages",
  abstract =     "A 'data crawler' is allowed to meander around an image
                 deciding what it considers to be interesting and laying
                 down flags in areas where its interest has been
                 aroused. These flags can be analysed statistically as
                 if the image was being viewed from afar to achieve
                 object recognition. The guidance program for the
                 crawler, the program which excites it to deposit a flag
                 and how the flags are combined statistically, are
                 driven by an evolutionary process which has as
                 objective the minimisation of misses and false alarms.
                 The crawler is represented by a tree-based Genetic
                 Programming (GP) method with fixed architecture
                 Automatically Defined Functions (ADFs). The crawler was
                 used as a post-processor to the object detection
                 obtained by a Staged GP method, and it managed to
                 appreciably reduce the number of false alarms on a
                 real-world application of vehicle detection in infrared
  notes =        "EvoWorkshops2002, part of cagnoni:2002:ews

                 READMEM WRITEMEM working memory. Mark decisions branch.
                 Flags. Second results branch. Looking for cars


Genetic Programming entries for Daniel Howard Simon C Roberts Conor Ryan