Program Size and Pixel Statistics in Genetic Programming for Object Detection

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{zhang2:evows04,
  author =       "Mengjie Zhang and Urvesh Bhowan",
  title =        "Program Size and Pixel Statistics in Genetic
                 Programming for Object Detection",
  booktitle =    "Applications of Evolutionary Computing,
                 EvoWorkshops2004: {EvoBIO}, {EvoCOMNET}, {EvoHOT},
                 {EvoIASP}, {EvoMUSART}, {EvoSTOC}",
  year =         "2004",
  month =        "5-7 " # apr,
  editor =       "Guenther R. Raidl and Stefano Cagnoni and 
                 Jurgen Branke and David W. Corne and Rolf Drechsler and 
                 Yaochu Jin and Colin R. Johnson and Penousal Machado and 
                 Elena Marchiori and Franz Rothlauf and George D. Smith and 
                 Giovanni Squillero",
  series =       "LNCS",
  volume =       "3005",
  address =      "Coimbra, Portugal",
  publisher =    "Springer Verlag",
  publisher_address = "Berlin",
  pages =        "379--388",
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 computation",
  ISBN =         "3-540-21378-3",
  DOI =          "doi:10.1007/978-3-540-24653-4_39",
  abstract =     "This paper describes an approach to the use of genetic
                 programming for object detection problems. In this
                 approach, local region pixel statistics are used to
                 form three terminal sets. The function set is
                 constructed by the four standard arithmetic operators
                 and a conditional operator. A multi-objective fitness
                 function is constructed based on detection rate, false
                 alarm rate, false alarm area and program size. This
                 approach is applied to three object detection problems
                 of increasing difficulty. The results suggest that the
                 concentric circular pixel statistics are more effective
                 than the square features for the coin detection
                 problems. The fitness function with program size is
                 more effective and more efficient for these object
                 detection problems and the evolved genetic programs
                 using this fitness function are much shorter and easier
                 to interpret.",
  notes =        "EvoWorkshops2004",
}

Genetic Programming entries for Mengjie Zhang Urvesh Bhowan

Citations