DocumentCode
2216325
Title
Selective motion detection by Genetic Programming
Author
Shi, Qiao ; Song, Andy
fYear
2011
fDate
5-8 June 2011
Firstpage
496
Lastpage
503
Abstract
Motion detection is a vital part of vision systems, either biological or computerized. Conventional motion detection methods in machine vision can differentiate moving objects from background, but cannot directly handle different types of motions. In this paper, we present Genetic Programming (GP) as a method which not only removes relatively stationary background, but also can be selective on what kind of motions to capture. Programs can be evolved to select a certain type of moving objects and ignore other motions. That is to select fast moving target and ignore slowing moving ones. Furthermore programs can be evolved to handle these tasks even when the camera itself is in relatively arbitrary motion. This general GP method does not require additional process to differentiate various types of motions.
Keywords
computer vision; genetic algorithms; motion estimation; genetic programming; machine vision; selective motion detection; vision system; Cameras; Detectors; Motion detection; Pixel; Training; Vehicles; Videos;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location
New Orleans, LA
ISSN
Pending
Print_ISBN
978-1-4244-7834-7
Type
conf
DOI
10.1109/CEC.2011.5949659
Filename
5949659
Link To Document