Tracking Object Positions in Real-time Video using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Will Smart and Mengjie Zhang",
  title =        "Tracking Object Positions in Real-time Video using
                 Genetic Programming",
  institution =  "Computer Science, Victoria University of Wellington",
  year =         "2004",
  number =       "CS-TR-04-13",
  address =      "New Zealand",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  URL =          "",
  abstract =     "the use of Genetic Programming (GP) to evolve programs
                 for tracking objects quickly in streaming video. A
                 small number of images, with located objects, are used
                 as training data and GP automatically performs
                 feature-selection on these images at the pixel level.
                 The use of feature functions is introduced, taking a
                 single offset argument, in contrast to the standard
                 feature terminal approach. The features include both
                 ``directionless'' intensity features and
                 ``directional'' edge detection features. The fitness
                 function rewards evolved programs that can move
                 training points, located on a grid around an object,
                 closer to the object. As such, a good program will also
                 be able to update an object position from frame to
                 frame for tracking. Two video sequences are examined,
                 with evolved programs tracking the left-eye and
                 forehead of a person successfully. The method is very
                 fast, tracking a frame in six or seven milliseconds on
                 a 2.6GHz PC.",

Genetic Programming entries for Will Smart Mengjie Zhang