References
- T. W. S. Chow and S. Y. Cho, “Industrial neural vision system for underground railway station platform surveillance,” Adv. Eng. Inform. 12, 73-83 (2002).
- A. C. Davies, H. Y. Jia, and S. A. Velastin, “Crowd monitoring using image processing,” Electr. Comm. Eng. J. 7, 37-47 (1995). https://doi.org/10.1049/ecej:19950106
- C. S. Reqazzoni, A. Tesei, and V. Murino, “A real-time vision system for crowding monitoring,” in Proc. Int. Conf. Industrial Electronics, Control, and Instrumentation (Maui, HI, USA, Nov. 1993), pp. 15-19.
- S. Y. Cho and T. W. S. Chow, “A fast neural learning vision system for crowd estimation at underground stations platform,” Neur. Proc. Lett. 10, 111-120 (1999). https://doi.org/10.1023/A:1018781301409
- S. A. Velastin, B. A. Boghssian, and M. A. Vicencio-Silva, “A motion-based image processing system for detecting potentially dangerous situations in underground railway stations,” Transp. Res. C Emerg. Technol. 14, 96-113 (2006). https://doi.org/10.1016/j.trc.2006.05.006
- S. Bouchafa, D. Aubert, and S. Bouzar, “Crowd motion estimation and motionless detection in subway corridors by image processing,” in Proc. IEEE Conf. Intelligent Transportation System (Boston, MA, USA, Nov. 1997), pp. 9-12.
- B. P. L. Lo and S. A Velastin, “Automatic congestion detection system for underground platforms,” in Proc. Int. Symp. Intelligent Multimedia, Video and Speech Processing (Hong Kong, China, Apr. 2001), pp. 158-161.
- C. Sacchi and C. S. Regazzoni, “A distributed surveillance system for detection of abandoned objects in unmanned railway environments,” IEEE Trans. Vehic. Technol. 49, 2013-2026 (2000). https://doi.org/10.1109/25.892603
- C. Seyve, “Metro railway security algorithms with real world experience adapted to the RATP dataset,” in Proc. IEEE Conf. Advanced Video and Signal Based Surveillance (Como, Italy, Sep. 2005), pp. 177-182.
- A. Cavallaro, “Event detection in underground stations using multiple heterogeneous surveillance cameras,” LNCS: Advanced in Visual Computing 3804, 535-542 (2005). https://doi.org/10.1007/11595755_65
- M. Spirito, C. S. Regazzoni, and L. Marcenaro, “Automatic detection of dangerous events for underground surveillance,” in Proc. IEEE Conf. Advanced Video and Signal Based Surveillance (Como, Italy, Sep. 2005), pp. 195-200.
- J. Black, S. Velastin, and B. Boghossian, “A real time surveillance system for metropolitan railways,” in Proc. IEEE Conf. Advanced Video and Signal Based Surveillance (Como, Italy, Sep. 2005), pp. 189-194.
- A. Bigdeli, B. C. Lowell, C. Sanderson, T. Shan, and S. Chen, “Vision processing in intelligent CCTV for mass transport security,” in Proc. IEEE Worksh. Singal Processing Applications for Public Security and Forensics (Washington D.C., USA, Apr. 2007), pp. 1-4.
- C. Carincotte, X. Naturel, M. Hick, J.-M. Odobez, J. Yao, A. Bastide, and B. Corbucci, “Understanding metro station usage using closed circuit television cameras analysis,” in Proc. Int. IEEE Conf. Intelligent Transportation Systems (Beijing, China, Oct. 2008), pp. 420-427.
- F. Ziliani, S. Velastin, F. Porikli, L. Marcenaro, T. Kelliher, A. Cavallaro, and P. Bruneaut, “Performance evaluation of event detection solutions: the CREDS experience,” in Proc. of IEEE Int. Conf. on Advanced Video and Signal Based Surveillance (Como, Italy, Sep. 2005), pp. 201-206.
- T. C. Wei, D. H. Shin, and B. G. Lee, “Resolution-enhanced reconstruction of 3D object using depth-reversed elemental imaes for partially occluded object recognition,” J. Opt. Soc. Korea 13, 139-145 (2009). https://doi.org/10.3807/JOSK.2009.13.1.139
- R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University Press, Cambridge, UK, 2000).
- K. C. Kwon, Y. T. Lim, and N. Kim, “Vergence control of binocular stereoscopic camera using disparity information,” J. Opt. Soc. Korea 13, 379-385 (2009). https://doi.org/10.3807/JOSK.2009.13.3.379
- Y. Sasaki and N. Hiura, “Development of image processing type fallen passenger detecting system,” JR EAST Technical Review 2, 66-72 (2003).