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Estimation of stereo camera motion

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents an algorithm for estimating the motion of a stereovision camera. The movement is calculated on the base of a sequence of depth pictures. While moving the camera can be held in hands without much impact on the prediction accuracy. The algorithm provides real-time data processing when a 2.5 GHz dual core computer is used.
Słowa kluczowe
Rocznik
Strony
27--31
Opis fizyczny
Bibliogr. 11 poz., tab., rys., fot.
Twórcy
  • Technical University of Lodz, Institute of Electronics
autor
  • Technical University of Lodz, Institute of Electronics
  • Technical University of Lodz, Institute of Electronics
Bibliografia
  • [1] Modsching, M., R. Kramer, and K. Hagen. “Field trial on GPS Accuracy in a medium size city: The influence of built-up”. Proceeding Of Th e 3rd Workshop On Positioning, Navigation And Communication (WPNC’06).
  • [2] Smith, R.C., and P. Cheeseman. “On the representation and estimation of spatial uncertainty”. International Journal of Robotics Research 5(4), 1986: 56–68.
  • [3] Montemerlo, M., et al. “FastSLAM2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges”. In Proc. International Joint Conference on Artifi cial Intelligence, 2003: 1151–1156.
  • [4] Cecelja, F., W. Balachandran, and R. Jirawimut. “A Stereo Vision System for Pedestrian Navigation”. 17th International Conference on Applied Electromagnetics and Commu ni ca tions. 1–3 October 2003. Dubrovnik, Croatia.
  • [5] Klein, G., and D. Murray. “Parallel Tracking and Mapping for Small AR Workspaces”. In Proc. International Symposium on Mixed and Augmented Reality (ISMAR’07, Nara).
  • [6] Rosten, E., and T. Drummond. “Machine learning for high-speed corner detection”. European Conference on Computer Vision 2006: 430–443.
  • [7] Lucas, D., T. Kanade, and C. Tomassi. “Kanade Feature Tracker”. http://www.ces.clemson.edu/~stb/klt/ (last visited may 2010).
  • [8] Fischler, M., and R. Bolles. “Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography”. Communications of the ACM 24(6), June 1981: 381–395.
  • [9] Skulimowski, P. “Segmentation and parametric description of scene objects in image sequences recorded form a mobile stereovision system, with the aim of auditory 3D scene presentation”. PhD Th esis, Technical University of Lodz, 2009 (In Polish).
  • [10] “The OpenCV project”. http://opencv.willowgarage.com/wiki/ (last visited may 2010).
  • [11] “The PointGrey”. http://www.ptgrey.com/products/bumblebee2/index.asp (last visited may 2010).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2030fcb8-9ebe-418c-9642-20d744f62ca9
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