Abstract
In this paper we discuss a problem of automatic analysis of vehicles trajectories in the context of illegal movements. It is crucial to detect restricted or security critical behaviour on roads, especially for safety protection and fluent traffic. Here, we propose an vision-based algorithm for vehicle detection and tracking, which is later employed to recognize patterns in resultant trajectories. Experiments were performed on real video streams. They gave encouraging results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aarthi, R., Padmavathi, S., Amudha, J.: Vehicle detection in static images using color and corner map. In: 2010 International Conference on Recent Trends in Information, Telecommunication and Computing, pp. 244–246 (2010)
Bradski, G.: Computer vision face tracking for use in a perceptual user interface. Intel Technol. J. Microcomputer Research Lab, Intel Corporation (1998)
Dubuisson, M.P., Jain, A.K.: A modified Hausdorff distance for object matching. In: Proceedings of the 12th IAPR International Conference on Pattern Recognition ICPR94, pp. 566–568, Jerusalem, Israel (1994)
Fabian, T.: Parking lot occupancy detection using computational fluid dynamics. In: Burduk, R., et al. (eds.) CORES 2013. AISC 226, pp. 733–742 (2013)
Forczmański, P., Seweryn, M.: Surveillance video stream analysis using adaptive background model and object recognition. Comput. Vis. Graph., LNCS 6374, 114–121 (2010)
Frejlichowski, D., Forczmański, P., Nowosielski, A., Gościewska, K., Hofman, R.: SmartMonitor: an approach to simple, intelligent and affordable visual surveillance system. In: Bolc, L., et al. (eds.) ICCVG 2012. LNCS, vol. 7594, pp. 726–734. Springer, Heidelberg (2012)
Frejlichowski, D., Gościewska, K., Forczmański, P., Nowosielski, A., Hofman, R.: Extraction of the foreground regions by means of the adaptive background modelling based on various colour components for a visual surveillance system. In: Burduk, R., et al. (eds.) CORES 2013. AISC 226, pp. 351–360. Springer, Heidelberg (2013)
Frejlichowski, D., Gościewska, K., Forczmański, P., Hofman, R.: SmartMonitor—an intelligent security system for the protection of individuals and small properties with the possibility of home automation. Sensors 14, 9922–9948 (2014)
Frejlichowski, D., Gościewska, K., Forczmański, P., Hofman, R.: Application of foreground object patterns analysis for event detection in an innovative video surveillance system. Pattern Anal. Appl. 1–12 (2014). doi:10.1007/s10044-014-0405-7
Hu, W., Xiao, X., Xie, D., Tan, T.: Traffic accident prediction using vehicle tracking and trajectory analysis. In: Intelligent Transportation Systems. Proceedings. 2003 IEEE, vol. 1, pp. 220–225 (2003)
Kovacic, K., Ivanjko, E., Gold, H.: Computer vision systems in road vehicles: a review. In: Proceedings of the Croatian Computer Vision Workshop, Year 1, pp. 25–30. Zagreb, Croatia (2013)
Miklasz, M., Nowosielski, A., Kawka, G.: Automated supervision systems for limited traffic zones. Arch. Transp. Syst. Telemat. 6(2), 41–45 (2013)
Mimbela, L.E.Y., Klein, L.A.: Summary of vehicle detection and surveillance technologies used in intelligent transportation systems. Federal Highway Administration’s (FHWA) Intelligent Transportation Systems Joint Program Office (2003)
Munuzuri, J., Corts, P., Guadix, J., Onieva, L.: City logistics in Spain: why it might never work. Cities 29(2), 133–141 (2012)
Pandit, V., Doshi, J., Mehta, D., Mhatre, A., Janardhan, A.: Smart traffic control system using image processing. Int. J. Emerg. Trends Technol. Comput. Sci. (IJETTCS) 3(1), 280–283 (2014)
Song, H.-S., Lu, S.-N., Ma, X., Yang, Y., Liu, X.-Q., Zhang, P.: Vehicle behavior analysis using target motion trajectories. IEEE Trans. Veh. Technol. 63(8), 3580–3591 (2014)
Tang, Y., Zhang, C., Gu, R., Li, P., Yang, B.: Vehicle detection and recognition for intelligent traffic surveillance system. Multimedia Tools and Applications (online). Springer (2015)
Viola, P., Jones, M.: Robust real-time object detection. In: Second International Workshop on Statistical and Computational Theories of Vision—Modeling, Learning, Computing, and Sampling, Vancouver, Canada (2001)
Wu, J., Cui, Z., Chen, J., Zhang, G.: A survey on video-based vehicle behavior analysis algorithms. J. Multimed. 7(3), 223–230 (2012)
Zajac, W., Kołopieńczyk, M., Andrzejewski, G.: Traffic load detection system. Arch. Transp. Syst. Telemat. 6(3), 46–48 (2013)
Acknowledgments
The project “Security system for public spaces—‘SM4Public’ prototype construction and implementation” (original title: Budowa i wdrożenie prototypu systemu bezpieczeństwa przestrzeni publicznej ‘SM4Public’) is a project co-founded by European Union (EU) (project number PL: POIG.01.04.00-32-244/13, value: 12.936.684,77 PLN, EU contribution: 6.528.823,81 PLN, realization period: 01.06.2014–31.10.2015). European Funds-for the development of innovative economy (Fundusze Europejskie-dla rozwoju innowacyjnej gospodarki).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Nowosielski, A., Frejlichowski, D., Forczmański, P., Gościewska, K., Hofman, R. (2016). Automatic Analysis of Vehicle Trajectory Applied to Visual Surveillance. In: Choraś, R. (eds) Image Processing and Communications Challenges 7. Advances in Intelligent Systems and Computing, vol 389. Springer, Cham. https://doi.org/10.1007/978-3-319-23814-2_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-23814-2_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23813-5
Online ISBN: 978-3-319-23814-2
eBook Packages: EngineeringEngineering (R0)