Vision-Based Vehicle Counting with High Accuracy for Highways with Perspective View

1. Shirazi, M.S., Morris, B.: A typical video-based framework for counting, behavior and safety analysis at intersections. In: Intelligent Vehicles Symposium (IV), pp. 1264–1269. IEEE (2015)

   Google Scholar 

2. Shirazi, M.S., Morris, B.: Observing behaviors at intersections: a review of recent studies and developments. In: Intelligent Vehicles Symposium (IV), pp. 1258–1263. IEEE (2015)

   Google Scholar 

3. Shirazi, M.S., Morris, B.: Vision-based turning movement counting at intersections by cooperating zone and trajectory comparison modules. In: Proceedings of 17th International IEEE Conference on Intelligent Transportation Systems, Qingdao, China, pp. 3100–3105 (2014)

   Google Scholar 

4. Bousetouane, F., Vandewiele, F., Motamed, C.: Occlusion management in distributed multi-object tracking for visual-surveillance. Pattern Recogn. Image Anal. 25, 295–300 (2015)

   Article  Google Scholar 

5. Lipton, A.J., Fujiyoshi, H., Patil, R.S.: Moving target classification and tracking from real-time video. In: Proceedings of Fourth IEEE Workshop Applications of Computer Vision, Princeton, New Jersey, pp. 8–14 (1998)

   Google Scholar 

6. Fang, W., Zhao, Y., Yuan, Y., Liu, K.: Real-time multiple vehicles tracking with occlusion handling. In: 2011 Sixth International Conference on Image and Graphics (ICIG), San Juan, Puerto Rico, pp. 667–672 (2011)

   Google Scholar 

7. Koller-Meier, E.B., Ade, F.: Tracking multiple objects using the condensation algorithm. J. Robot. Auton. Syst. 34, 93–105 (2001)

   Article  MATH  Google Scholar 

8. Sun, Z., Bebis, G., Miller, R.: Monocular precrash vehicle detection: features and classifiers. IEEE Trans. Image Process. 15, 2019–2034 (2006)

   Article  Google Scholar 

9. Sun, Z., Bebis, G., Miller, R.: On road vehicle detection using gabor filters and support vector machines. In: Proceeding of the IEEE International Conference in Digital Signal Processing, pp. 1019–1022 (2002)

   Google Scholar 

10. Teoh, S.S., Braunl, T.: Symmetry-based monocular vehicle detection system. J. Mach. Vis. Appl. 23, 831–842 (2012)

    Article  Google Scholar 

11. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Proceeding of IEEE Conference on Computer Vision and Pattern Recognition (2005)

    Google Scholar 

12. Shirazi, M.S., Morris, B.: Contextual combination of appearance and motion for intersection videos with vehicles and pedestrians. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., McMahan, R., Jerald, J., Zhang, H., Drucker, S.M., Kambhamettu, C., El Choubassi, M., Deng, Z., Carlson, M. (eds.) ISVC 2014, Part I. LNCS, vol. 8887, pp. 708–717. Springer, Heidelberg (2014)

    Google Scholar 

13. Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2, 1–27 (2011)

    Article  Google Scholar 

14. Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 246–252 (1999)

    Google Scholar 

15. Rtc/fast live freeway traffic cams. (http://www.rtcsnv.com/fast-cam/)

Download references