Pixel Statistics and Program Size in Genetic Programming for Object Detection

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

  author =       "Mengjie Zhang and Urvesh Bhowan",
  title =        "Pixel Statistics and Program Size in Genetic
                 Programming for Object Detection",
  institution =  "Computer Science, Victoria University of Wellington",
  year =         "2004",
  number =       "CS-TR-04-3",
  address =      "New Zealand",
  keywords =     "genetic algorithms, genetic programming, pixel
                 statistics, false alarm position, program size,
                 multiclass object detection",
  URL =          "http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-04/CS-TR-04-3.pdf",
  URL =          "http://www.mcs.vuw.ac.nz/comp/Publications/CS-TR-04-3.abs.html",
  abstract =     "genetic programming for object detection problems. In
                 this approach, domain independent, 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
                 position 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 these object 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

Genetic Programming entries for Mengjie Zhang Urvesh Bhowan