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Application of the HDR imaging in vehicles’ video tracking systems

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Języki publikacji
EN
Abstrakty
EN
Video systems are used in Intelligent Transportation Systems for vehicles’ tracking. Cameras typically used in these systems are characterized by relatively low dynamic range which is only a fragment of the dynamic range of the human eye. In order to adapt to the lighting conditions the cameras feature dynamic changes of the gain and exposure. For vehicles there is a very wide range of the observed brightness of details because of the variety of vehicles’ colors and the presence of elements reflecting light in different ways, as well as changing lighting conditions. This means that even if the camera is able to capture the relevant dynamic range, there is a restriction of the distinguishability of details, which is essential in the process of detecting the location of vehicles. The use of HDR imaging techniques based on various exposures helps to increase the dynamic range and improves the accuracy of vehicles’ positions estimation.
Rocznik
Strony
32--36
Opis fizyczny
Bibliogr. 13 poz.
Twórcy
autor
autor
  • Faculty of Motor Transport, Higher School of Technology and Economics in Szczecin, Klonowica 14, 71-244 Szczecin, Poland, okarma@wste.szczecin.pl
Bibliografia
  • 1. KLEIN L.A., Sensor Technologies and Data Requirements for ITS. Artech House ITS library, Norwood, Massachusetts 2001.
  • 2. KLEIN L.A., MILLS M.K., GIBSON D.R.P., Traffic Detector Handbook: Third Edition - Volume I, FHWA-HRT-06-108, FHWA, 2006.
  • 3. KNOLL P., HDR Vision for Driver Assistance. In: High Dynamic Range (HDR) Vision, B. Hoefflinger (ed.), p.123-136, Springer 2007.
  • 4. SEGER U., KNOLL P.M., STILLER C., Sensor Vision and Collision Warning Systems, Convergence Conference, Detroit 2000.
  • 5. SCHNEIDER K., ZIMMERMANN H.K., Highly Sensitive Optical Receivers, Springer 2006.
  • 6. MYSZKOWSKI K., MANTIUK R., KRAWCZYK G., High Dynamic Range Video. Morgan & Claypool Publishers 2008.
  • 7. WANGY H., RASKARZ R., AHUJA N.: High Dynamic Range Video Using Split Aperture Camera. Proceeding of the 6-th IEEE Workshop on Omnidirectional Vision, Camera Networks and Non-classical cameras OMNIVIS’05, 2005.
  • 8. OKARMA K., MAZUREK P., Background Estimation Algorithm for Optical Car Tracking Applications. Machinebuilding and Electrical Engineering no. 7-8, p. 7-10, 2006.
  • 9. BLACKMAN S., POPOLI R., Design and Analysis of Modern Tracking Systems, Artech House, 1999.
  • 10. BROOKNER E., Tracking and Kalman Filtering Made Easy, Wiley 1998.
  • 11. KALMAN R.E., A New Approach to Linear Filtering and Prediction Problems. Journal of Basic Engineering vol. 82 no. 1, p.35-45, 1960.
  • 12. REINHARD E., WARD G., PATTANAIK S., DEBEVEC P. High Dynamic Range Imaging Acquisition, Display, and Image-Based Lighting, Elsevier 2005.
  • 13. WARD G.: Fast Robust Image Registration for Compositing High Dynamic Range Photographs from Hand-Held Exposures, Journal of Graphics Tools, vol. 8 no .2, p.17-30, 2003.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSL8-0042-0017
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