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Description
  • 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
  • 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 (en)
Title
  • Energy based descriptors and their application for car detection
  • Energy based descriptors and their application for car detection (en)
skos:prefLabel
  • Energy based descriptors and their application for car detection
  • Energy based descriptors and their application for car detection (en)
skos:notation
  • RIV/61989100:27240/14:86093009!RIV15-MSM-27240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 14584
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/14:86093009
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • recognition; object detection; image features (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [FDF40A976280]
http://linked.open...v/mistoKonaniAkce
  • Lisabon
http://linked.open...i/riv/mistoVydani
  • [Portugalsko]
http://linked.open...i/riv/nazevZdroje
  • VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Fusek, Radovan
  • Mozdřeň, Karel
  • Sojka, Eduard
  • Šurkala, Milan
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://bibframe.org/vocab/doi
  • 10.5220/0004685804920499
http://purl.org/ne...btex#hasPublisher
  • SciTePress - Science and Technology Publications
https://schema.org/isbn
  • 978-989-758-003-1
http://localhost/t...ganizacniJednotka
  • 27240
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