Engineering of Computer Vision Algorithms Using Evolutionary Algorithms
Inhaltsverzeichnis
Reference
Marc Ebner: Engineering of Computer Vision Algorithms Using Evolutionary Algorithms. Proceedings of the 11th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2009, Lecture Notes in Computer Science, Vol. 5807, pp. 367-378, Springer, September 28- October 2 2009.
DOI
http://dx.doi.org/10.1007/978-3-642-04697-1_34
Abstract
Computer vision algorithms are currently developed by looking up the available operators from the literature and then arranging those operators such that the desired task is performed. This is often a tedious process which also involves testing the algorithm with different lighting conditions or at different sites. We have developed a system for the automatic generation of computer vision algorithms at interactive frame rates using GPU accelerated image processing. The user simply tells the system which object should be detected in an image sequence. Simulated evolution, in particular Genetic Programming, is used to automatically generate and test alternative computer vision algorithms. Only the best algorithms survive and eventually provide a solution to the user’s image processing task.
Extended Abstract
Bibtex
Used References
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http://www.ra.cs.uni-tuebingen.de/mitarb/ebner/research/publications/uniTu2/EvoCVengineering.pdf
