Wizyjna detekcja obiektów w obrazach przy użyciu klasyfikatora SVM i deskryptorów HOG : porównanie wyników dla kolejowych sygnalizatorów świetlnych oraz dla sylwetek ludzkich

Journal Title: Autobusy. Technika, Eksploatacja, Systemy Transportowe - Year 2017, Vol 214, Issue 12

Abstract

In this paper Detection-Error Tradeoff Curves were compared for the single SVM classifier which was tested on the set of images containing railway traffic lights using the software which Authors implemented in Matlab, software implemented by the Authors in OpenCV (C++) and for the single SVM classifier tested on the INRIA persons image set using software implemented by the Authors in Matlab. Research performed in this paper are important because in the last numerical experiments high values of FPPW coefficient (False Positives Per Window) were obtained. Results presented in this paper prove that characteristic features of the railway traffic lights geometry do not influence value of FPPW and HOG descriptors can be successfully used for this type of object.

Authors and Affiliations

Roman Król, Piotr Bojarczak, Adam Taraś

Keywords

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  • EP ID EP407588
  • DOI -
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How To Cite

Roman Król, Piotr Bojarczak, Adam Taraś (2017). Wizyjna detekcja obiektów w obrazach przy użyciu klasyfikatora SVM i deskryptorów HOG : porównanie wyników dla kolejowych sygnalizatorów świetlnych oraz dla sylwetek ludzkich. Autobusy. Technika, Eksploatacja, Systemy Transportowe, 214(12), 260-263. https://europub.co.uk./articles/-A-407588