Towards Automated Learning of Object Detectors

Created by W.Langdon from gp-bibliography.bib Revision:1.7662

@InProceedings{Ebner:2010:EvoIASP,

• author = "Marc Ebner",
• title = "Towards Automated Learning of Object Detectors",
• booktitle = "EvoIASP",
• year = "2010",
• editor = "Cecilia {Di Chio} and Stefano Cagnoni and Carlos Cotta and Marc Ebner and Aniko Ekart and Anna I. Esparcia-Alcazar and Chi-Keong Goh and Juan J. Merelo and Ferrante Neri and Mike Preuss and Julian Togelius and Georgios N. Yannakakis",
• volume = "6024",
• series = "LNCS",
• pages = "231--240",
• address = "Istanbul",
• month = "7-9 " # apr,
• organisation = "EvoStar",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming, GPU",
• isbn13 = "978-3-642-12238-5",
• DOI = "doi:10.1007/978-3-642-12239-2_24",
• abstract = "Recognizing arbitrary objects in images or video sequences is a difficult task for a computer vision system. We work towards automated learning of object detectors from video sequences (without user interaction). Our system uses object motion as an important cue to detect independently moving objects in the input sequence. The largest object is always taken as the teaching input, i.e. the object to be extracted. We use Cartesian Genetic Programming to evolve image processing routines which deliver the maximum output at the same position where the detected object is located. The graphics processor (GPU) is used to speed up the image processing. Our system is a step towards automated learning of object detectors.",
• notes = "EvoIASP'2010 held in conjunction with EuroGP'2010 EvoCOP2010 EvoBIO2010",

}

Genetic Programming entries for Marc Ebner

Citations