Evolving Frame Splitters by Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Feng:2012:CEC,

• title = "Evolving Frame Splitters by Genetic Programming",
• author = "Xie Feng and Andy Song",
• pages = "1466--1472",
• booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary Computation",
• year = "2012",
• editor = "Xiaodong Li",
• month = "10-15 " # jun,
• DOI = "doi:10.1109/CEC.2012.6256161",
• address = "Brisbane, Australia",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, Evolutionary Computer Vision",
• abstract = "This paper extends the application of Genetic Programming into a new area, automatically splitting video frames based on the content. A GP methodology is presented to show how to evolve a program which can analyse the difference between scenes and split them accordingly. A few different approaches have been investigated in this study. Compared with human written video splitting programs, GP generated splitters are more accurate. Moreover, it is shown that these video splitting programs have high tolerance to noises. They can still achieve reasonable performance even when the videos are not easily recognisable by eyes due to the server artificial noises.",
• notes = "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the EPS and the IET.",

}

Genetic Programming entries for Feng Xie Andy Song

Citations