Tracking Object Positions in Real-time Video using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@TechReport{vuw-CS-TR-04-13,

• 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 = "http://www.mcs.vuw.ac.nz/comp/Publications/CS-TR-04-13.abs.html",
• URL = "http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-04/CS-TR-04-13.pdf",
• 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

Citations