• DocumentCode
    3669561
  • Title

    Energy based descriptors and their application for car detection

  • Author

    Radovan Fusek;Eduard Sojka;Karel Mozdřeň;Milan Šurkala

  • Author_Institution
    Technical University of Ostrava, FEECS, Department of Computer Science, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic
  • Volume
    1
  • fYear
    2014
  • Firstpage
    492
  • Lastpage
    499
  • Abstract
    In this paper, we propose a novel technique for object description. The proposed method is based on investigation of energy distribution (in the image) that describes the properties of objects. The energy distribution is encoded into a vector of features and the vector is then used as an input for the SVM classifier. Generally, the technique can be used for detecting arbitrary objects. In this paper, however, we demonstrate the robustness of the proposed descriptors for solving the problem of car detection. Compared with the state-of-the-art descriptors (e.g. HOG, Haar-like features), the proposed approach achieved better results, especially from the viewpoint of dimensionality of the feature vector; the proposed approach is able to successfully describe the objects of interest with a relatively small set of numbers without the use of methods for the reduction of feature vector.
  • Keywords
    "Detectors","Feature extraction","Automobiles","Temperature distribution","Support vector machines","Training","Image edge detection"
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision Theory and Applications (VISAPP), 2014 International Conference on
  • Type

    conf

  • Filename
    7294849