Zhenhua Pan, Kewei Li, Hongbin Deng, and Yiran Wei


  1. [1] T. Xia, M. Yang, R. Yang, and C. Wang, Cyber C3: A proto type cybernetic transportation system for urban applications, IEEE Transactions on Intelligent Transportation Systems, 11(1), 2010, 142–152.
  2. [2] S. Jingzhuo, L. Yu, H. Jingtao, X. Meiyu, Z. Juwei, and Z. Lei, Novel intelligent PID control of traveling wave ultrasonic motor, ISA Transactions, 53(5), 2014, 1670–1679.
  3. [3] J. Dickmann, K. Dietmayer, and M. Rapp, Probabilistic egomotion estimation using multiple automotive radar sensors, Robotics and Autonomous Systems, 89, 2017, 136–146.
  4. [4] A.M. Neto, A.C. Victorino, I. Fantoni, and J.V. Ferreira, Real-time estimation of drivable image area based on monocular vision, 2013 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), Gold Coast, QLD, 2013, 63–68, doi: 10.1109/IVWorkshops.2013.6615227.
  5. [5] S. Sivaraman and M.M. Trivedi, Looking at vehicles on the road: A survey of vision-based vehicle detection, tracking, and behavior analysis, IEEE Transactions on Intelligent Transportation Systems, 14(4), 2013, 1773–1795.
  6. [6] C. Wang,Y Fang, H. Zhao, C. Guo, S. Mita, and H. Zha, Probabilistic inference for occluded and multi-view on-road vehicle detection, IEEE Transactions on Intelligent Transportation systems, 17(1), 2016, 215–229.
  7. [7] Z. Li, W. Zhou, L. Chen, and S. Jin, Bio-inspired approach for image vehicle detection under low illumination, International Journal of Robotics & Automation, 35(5), 2020, 332–338.
  8. [8] S. Sugimoto, H. Tateda, H. Takahashi, and M. Okutomi, Obstacle detection using millimeter-wave radar and its visualization on image sequence, Proceedings of the 17th International Conference on Pattern Recognition, 2004 (ICPR 2004), Cambridge, MA, Vol. 3, 2004, 342–345. doi: 10.1109/ICPR.2004.1334537.
  9. [9] G. Liu, M. Zhou, L. Wang, H. Wang, and X. Guo, A blind spot detection and warning system based on millimeter wave radar for driver assistance, Optik-International Journal for Light and Electron Optics, 135, 2017, 353–365.
  10. [10] M. Bogdan, T. Ruxandra, and Z. Titus, When ultrasonic sensors and computer vision join forces for efficient obstacle detection and recognition, Sensors, 16(12), 2016, 1807.
  11. [11] Y. Su, Y. Zhang, J.M. Alvarez, and H. Kong, An illumination-invariant nonparametric model for urban road detection using monocular camera and single-line lidar, 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), Macau, 2017, 68–73, doi: 10.1109/ROBIO.2017.8324396.
  12. [12] S. Budzan and J. Kasprzyk, Fusion of 3D laser scanner and depth images for obstacle recognition in mobile applications, Optics and Lasers in Engineering, 77, 2016, 230–240.
  13. [13] L. Basaca-Preciado, O. Sergiyenko, J. Rodr´ıguez-Qui˜nonez, and X. Garc´ıa, Optical 3D laser measurement system for navigation of autonomous mobile robot, Optics and Lasers in Engineering, 54, 2014, 159–169.
  14. [14] J. Zhang, B. Yang, N. Geng, and L. Huang, An obstacle detection system based on monocular vision for apple orchard robot, International Journal of Robotics & Automation, 32(6), 2017, 639–648.
  15. [15] F. Garc´ıa, A. Prioletti, P. Cerri, and A. Broggi, PHD filter for vehicle tracking based on a monocular camera, Expert Systems with Applications, 91, 2018, 472–479.
  16. [16] G. Aragon-Camarasa, H. Fattah, and J.P. Siebert, Towards a unified visual framework in a binocular active robot vision system, Robotics and Autonomous Systems, 58(3), 2010, 276–286.186
  17. [17] M. Perrollaz, R. Labayrade, D. Gruyer, A. Lambert, and D. Aubert, Proposition of generic validation criteria using stereovision for on-road obstacle detection, International Journal of Robotics &Automation, 29(1), 2014, 32–43.
  18. [18] A. Broggi, A. Fascioli, M. Carletti, T. Graf, and M. Meinecke, A multi-resolution approach for infrared vision-based pedestrian detection, IEEE Intelligent Vehicles Symposium, Parma, Italy, 2004, 7–12.
  19. [19] C. Otto, W. Gerber, F.P. Leon, and J. Wirnitzer, A joint integrated probabilistic data association filter for pedestrian tracking across blind regions using monocular camera and radar, 2012 IEEE Intelligent Vehicles Symposium, Alcala de Henares, 2012, 636–641.
  20. [20] Z. Ji and D. Prokhorov, Radar-vision fusion for object classification, IEEE, Proceedings of the 11th International Conference on Information Fusion Cologne Germany, 2008, 1–7.
  21. [21] D.M. Gavrila, J. Giebel, and S. Munder, Vision-based pedestrian detection: The PROTECTOR system, IEEE Intelligent Vehicles Symposium, Parma, Italy, 2004, 13–18.
  22. [22] G. Alessandretti, A. Broggi, and P. Cerri, Vehicle and guard rail detection using radar and vision data fusion, IEEE Transactions on Intelligent Transportation Systems, 8, 2007, 95–105.
  23. [23] U. Kadow, G. Schneider, and A. Vukotich, Radar-vision based vehicle recognition with evolutionary optimized and boosted features, 2007 IEEE Intelligent Vehicles Symposium, Istanbul, 2007, 749–754.
  24. [24] B. Bhanu, B. Roberts, and J. Ming, Inertial navigation sensor integrated motion analysis for obstacle detection, IEEE International Conference on Robotics and Automation, Cincinnati, OH, Vol. 5, no. 2, 1990, 954–959.
  25. [25] S. Wender and K. Dietmayer, 3D vehicle detection using a laser scanner and a video camera, IET Intelligent Transport Systems, 2(2), 2008, 105–112.
  26. [26] X. Wang, L. Xu, H. Sun, J. Xin, and N. Zheng, On-road vehicle detection and tracking using MMW radar and monovision fusion, IEEE Transactions on Intelligent Transportation Systems, 17(7), 2016, 2075–2084.
  27. [27] M. Jelavic, V. Petrovic, and N. Peric, A practical method for calibration of laser radar and camera based on double parallel planes, Journal of Central South University (Science and Technology), 43(12), 2012, 4735–4742.
  28. [28] D. Gao, J. Duan, X. Yang, and B. Zheng, A method of spatial calibration for camera and radar, 2010 8th World Congress on Intelligent Control and Automation, Jinan, 2010, 6211–6215.
  29. [29] H. Li, M. Yang, and H. Qian, Camera and laser scanner co-detection of pedestrians, 2011.
  30. [30] A. Mendes and U. Nunes, Situation-based multi-target detection and tracking with laser scanner in outdoor semi-structured environment, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No. 04CH37566), Sendai, Vol. 1, 2004, 88–93.
  31. [31] N. Dalal and B. Triggs, Histograms of oriented gradients for human detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), San Diego, CA, 2005, 886–893.

Important Links:

Go Back