Towards Automated Learning of Object Detectors

  • Marc Ebner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6024)


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.


Genetic Program Video Sequence Motion Vector Object Detector Computer Vision System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Marc Ebner
    • 1
  1. 1.Eberhard-Karls-Universität TübingenWilhelm-Schickard-Institut für InformatikTübingenGermany

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