Abstract
Geolocation information is not only crucial in conventional crime investigation, but also increasingly important for digital forensics as it allows for the logical fusion of digital evidence that is often fragmented across disparate mobile assets. This, in turn, often requires the reconstruction of mobility patterns. However, real-time surveillance is often difficult and costly to conduct, especially in criminal scenarios where such process needs to take place clandestinely. In this paper, we consider a vehicular tracking scenario and we propose an offline post hoc vehicular trace reconstruction mechanism that can accurately reconstruct vehicular mobility traces of a target entity by fusing the corresponding available visual and radio-frequency surveillance data. The algorithm provides a probabilistic treatment to the problem of incomplete data by means of Bayesian inference. In particular, we realize that it is very likely that a reconstructed route of a target entity will contain gaps (due to missing trace data), so we try to probabilistically fill these gaps. This allows law enforcement agents to conduct off-line tracking while characterizing the quality of available evidence.
Chapter PDF
Similar content being viewed by others
References
Tan, M., Tian, G.L., Ng, K.W.: Bayesian Missing Data Problems: EM, Data Agumentation and Noniterative Computation. CRC Press, Boca Raton (2009)
Calbi, A., Marcenaro, L., Regazzoni, C.: Dynamic Scene Reconstruction for 3D Virtual Guidance. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds.) KES 2006. LNCS (LNAI), vol. 4252, pp. 179–186. Springer, Heidelberg (2006)
Conaire, C.O., Fogarty, K., Brennan, C., O’Connor, N.E.: User Localisation using Visual Sensing and RF Signal Strength. In: ImageSese (2008)
Barakatsoulas, S., Pfoser, D., Salas, R., Wenk, C.: On Map-Matching Vehicle Tracking Data. In: VLDB ’05: Proceedings of the 31st international conference on Very large data bases, VLDB Endowment , pp. 853–864 (2005)
Al-Kuwari, S., Wolthusen, S.: A Survey of Forensic Localization and Tracking Mechanisms in Short-Range and Cellular Networks. In: Goel, S. (ed.) 1st International Conference on Digital Forensics & Cyber crime (ICDF2C), vol. 31, pp. 19–32 (2009)
Bay, H., Tuytelaars, T., Van Gool, L.: SURF: Speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)
Tanenbaum, A.: Computer Networks. Pearson Education Ltd., London (2003)
Miyajima, C., Nishiwaki, Y., Ozawa, K., Wakita, T., Itou, K., Takeda, K., Itakura, F.: Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Idenfication. Proeedings of the IEEE 95(2), 427–437 (2007)
Al-Kuwari, S., Wolthusen, S.: Forensics Tracking and Mobility Prediction in Vehicular Networks. In: Sixth Annual IFIP WG11.9 International Conference on Digital Forensics (2010)
Harri, J., Fiore, M., Fethi, F., Bonnet, C.: VanetMobiSim: Generating Realistic Mobility Patterns for VANETs. In: Proc. of the 3rd ACM International Workshop on Vehicular Ad Hoc Networks (VANET’06), Los Angeles, USA (2006)
Fiore, M., Harri, J., Filali, F., Bonnet, C.: Vehicular Mobility Simulation for VANETs. In: ANSS ’07: Proceedings of the 40th Annual Simulation Symposium, pp. 301–309. IEEE Computer Society, Los Alamitos (2007)
Treiber, M., Hennecke, A., Helbing, D.: Congested Traffic States in Empirical Observations and Microscopic Simulations. Physical Review E 62(2), 1805–18024 (2000)
Information Sciences Institute (NS-2 ), http://www.isi.edu/nsnam/ns
Wahab, A., Quek, C., Tan, C.K., Takeda, K.: Driving Profile Modeling and Recognition Based on Soft Computing Approach. IEEE Transactions on Neural Networks 20(4), 563–582 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Al-Kuwari, S., Wolthusen, S.D. (2010). Probabilistic Vehicular Trace Reconstruction Based on RF-Visual Data Fusion. In: De Decker, B., Schaumüller-Bichl, I. (eds) Communications and Multimedia Security. CMS 2010. Lecture Notes in Computer Science, vol 6109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13241-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-13241-4_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13240-7
Online ISBN: 978-3-642-13241-4
eBook Packages: Computer ScienceComputer Science (R0)