Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 10
Number of items: 10
  • Open Access
    Flohr, F. B. (2018). Vulnerable road user detection and orientation estimation for context-aware automated driving. [Thesis, fully internal, Universiteit van Amsterdam].
  • Kooij, J. F. P., Englebienne, G., & Gavrila, D. M. (2015). Identifying Multiple Objects from their Appearance in Inaccurate Detections. Computer Vision and Image Understanding, 136, 103-116. https://doi.org/10.1016/j.cviu.2015.03.012
  • Flohr, F., Dumitru-Guzu, M., Kooij, J. F. P., & Gavrila, D. M. (2015). A probabilistic framework for joint pedestrian head and body orientation estimation. IEEE Transactions on Intelligent Transportation Systems, 16(4), 1872-1882. https://doi.org/10.1109/TITS.2014.2379441
  • Open Access
    Kooij, J. F. P. (2015). Generative models for pedestrian track analysis. [Thesis, fully internal, Universiteit van Amsterdam].
  • Kooij, J. F. P., Schneider, N., & Gavrila, D. M. (2014). Analysis of Pedestrian Dynamics from a Vehicle Perspective. In 2014 IEEE Intelligent Vehicles Symposium (IV): June 8-11, 2014, Dearborn, Michigan, USA (pp. 1445-1450). IEEE. https://doi.org/10.1109/IVS.2014.6856505
  • Flohr, F., Dumitru-Guzu, M., Kooij, J. F. P., & Gavrila, D. M. (2014). Joint probabilistic head and body orientation estimation. In 2014 IEEE Intelligent Vehicles Symposium (IV): June 8-11, 2014, Dearborn, Michigan, USA (pp. 617-622). IEEE. https://doi.org/10.1109/IVS.2014.6856532
  • Open Access
    Kooij, J. F. P., Schneider, N., Flohr, F., & Gavrila, D. M. (2014). Context-based Pedestrian Path Prediction. In D. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Computer Vision – ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014: proceedings (Vol. VI, pp. 618-633). (Lecture Notes in Computer Science; Vol. 8694). Springer. https://doi.org/10.1007/978-3-319-10599-4_40
  • Kooij, J. F. P., Englebienne, G., & Gavrila, D. M. (2012). A non-parametric hierarchical model to discover behavior dynamics from tracks. In A. Fitzgibbon, S. Lazebnik, P. Perona, Y. Sato, & C. Schmid (Eds.), Computer Vision – ECCV 2012: 12th European Conference on Computer Vision: Florence, Italy, October 7-13, 2012: proceedings (Vol. 6, pp. 270-283). (Lecture Notes in Computer Science; Vol. 7577). Springer. https://doi.org/10.1007/978-3-642-33783-3_20
  • Oliehoek, F. A., Kooij, J. F. P., & Vlassis, N. (2008). A Cross-Entropy Approach to Solving Dec-POMDPs. In C. Badica, & M. Paprzycki (Eds.), Advances in Intelligent and Distributed Computing: proceedings of the 1st International Symposium on Intelligent and Distributed Computing IDC'2007, Craiova, Romania, October 2007 (pp. 145-154). (Studies in Computational Intelligence; Vol. 78). Springer. https://doi.org/10.1007/978-3-540-74930-1_15
  • Open Access
    Oliehoek, F. A., Kooij, J. F. P., & Vlassis, N. (2008). The cross-entropy method for policy search in decentralized POMDPs. Informatica, 32(4), 341-357. http://www.informatica.si/index.php/informatica/article/view/208
Page of