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Practical camera calibration and image rectification in monocular road traffic applications

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Wybrane pełne teksty z tego czasopisma
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Języki publikacji
EN
Abstrakty
EN
In this paper we follow apractical approach to the problem of camera calibration and image formation in a typical computer vision based traffic monitoring system. Our study starts by analysing in detail the capturing scenario and the undesirable effects resulting from the application of the pin-hole camera model to traffic images. Based on the acquired experience, we present an integral method to obtain the transformation matrices required to calibrate the camera and to construct in real time a rectified and sub-sampled image where perspective effects on the road plane have been removed. The motivation for this perspective-free image is to reduce the amount of data which must be computed (while avoiding loss of relevant information), remove influences from objects external to the capturing area and simplify the operation of the subsequent detection and tracking stages. The latter statement is justified since vehicle shapes can now be approximated by rectangles, the distance between any two neighbouring points on the road plane remains constant all over the image, and parallel trajectories are restored in the rectified image.
Twórcy
  • Universidad Nacional de Educación a Distancia, UNED. ETSI Informática, Madrid, Spain.
Bibliografia
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  • [11] Boult T., Micheals R., Gao X., Eckmann M.: Into the woods: Visual surveillance of noncooperative and camouflaged tragets in complex outdoor settings. Proc. of the IEEE, vol. 89, Oct., 1382-1402, 2001.
  • [12] Kamijo S., Ikeuchi K., Sakauchi M.: Vehicle tracking in low-angle and front-view images based on spatio-temporal markov random field model. 8th World Congress on ITS., Sydney, October, 2001.
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  • [16] Iera A., Modafferi A., Musolino G., Vitetta A.: An experimental station for real-time traffic monitoring on a urban road. IEEE 5th International Conference on Intelligent Transportation Systems, 697-70, 2002.
  • [17] Zang Q., Klette R.: Object classification and tracking in video surveillance. CAIP, 198-205, 2003.
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  • [19] Rodriguez T.: Adaptive real-time segmentation in traffic sequences, Machine Graphics & Vision Journal; 13(1), 39-52, 2004.
  • [20] Melo J., Naftel A., Bernardino A., Santos-Victor J.: Viewpoint independent detection of vehicle trajectories and lane geometry from uncalibrated traffic surveillance cameras. ICIAR (2), 454-462, 2004.
  • [21] Huang M.-C., Yen S. H.: A real-time and color-based computer vision for traffic monitoring system. IEEE International Conference on Multimedia and Expo, June, 2119-2122, 2004.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA0-0016-0004
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