Automatic detection of long term parked cars

AVSS 2015 - 12th IEEE International Conference on Advanced Video and Signal Based Surveillance

Volumn , Issue , 2015, Pages

  Carletti, Vincenzo ^a   Foggia, Pasquale ^a   Greco, Antonio ^a   Saggese, Alessia ^a   Vento, Mario ^a  

^a UNIVERSITY OF SALERNO   (Italy)

Author keywords

Data mining; Heating; Positron emission tomography; Signal processing algorithms; Trajectory; Vehicles; Videos

Indexed keywords

DATA MINING; HEATING; INTELLIGENT SYSTEMS; MONITORING; POSITRON EMISSION TOMOGRAPHY; SIGNAL DETECTION; SIGNAL PROCESSING; TRAFFIC CONGESTION; TRAJECTORIES; VEHICLES; VIDEO SIGNAL PROCESSING;

AUTOMATIC DETECTION; HEAT MAPS; INTELLIGENT TRANSPORTATION SYSTEMS; SIGNAL PROCESSING ALGORITHMS; SPATIOTEMPORAL INFORMATION; STATE OF THE ART; SURVEILLANCE CAMERAS; VIDEOS;

SECURITY SYSTEMS;

EID: 84958590884     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AVSS.2015.7301722     Document Type: Conference Paper

References (24)

1. A. Albiol, L. Sanchis, and J. M. Mossi. Detection of parked vehicles using spatiotemporal maps. Intelligent Transportation Systems, IEEE Transactions on, 12 (4): A1277-1291, 2011.
2. A. Bevilacqua and S. Vaccari. Real time detection of stopped vehicles in traffic scenes. In Advanced Video and Signal Based Surveillance, 2007. AVSS 2007. IEEE Conference on, pages 266-270. IEEE, 2007.
3. S. Boragno, B. Boghossian, J. Black, D. Makris, and S. Velastin. A dsp-based system for the detection of vehicles parked in prohibited areas. In Advanced Video and Signal Based Surveillance, 2007. AVSS 2007. IEEE Conference on, pages 260-265. IEEE, 2007.
4. L. Brown. Example-based color vehicle retrieval for surveillance. In Advanced Video and Signal Based Surveillance (AVSS), 2010 Seventh IEEE International Conference on, pages 91-96, Aug 2010.
5. L. Brun, A. Saggese, and M. Vento. Dynamic scene understanding for behavior analysis based on string kernels. Circuits and Systems for Video Technology, IEEE Transactions on, 24 (10): A1669-1681, Oct 2014.
6. A. d'Acierno, A. Saggese, and M. Vento. Designing huge repositories of moving vehicles trajectories for efficient extraction of semantic data. Intelligent Transportation Systems, IEEE Transactions on, PP (99): A1-12, 2015.
7. R. Di Lascio, P. Foggia, G. Percannella, A. Saggese, and M. Vento. A real time algorithm for people tracking using contextual reasoning. Computer Vision and Image Understanding, 117 (8): A892-908, Aug. 2013.
8. R. H. Evangelio, M. Patzold, and T. Sikora. A system for automatic and interactive detection of static objects. In Person-Oriented Vision (POV), 2011 IEEE Workshop on, pages 27-32. IEEE, 2011.
9. Q. Fan, S. Pankanti, and L. Brown. Long-term object tracking for parked vehicle detection. In IEEE AVSS, pages 223-229, Aug 2014.
10. R. Feris, B. Siddiquie, J. Petterson, Y. Zhai, A. Datta, L. Brown, and S. Pankanti. Large-scale vehicle detection, indexing, and search in urban surveillance videos. Multimedia, IEEE Transactions on, 14 (1): A28-42, Feb 2012.
11. E. Herrero-Jaraba, C. Orrite-Uruuela, and J. Senar. Detected motion classification with a double-background and a neighborhood-based difference. Pattern Recognition Letters, 24 (12): A2079-2092, 2003.
12. i LIDS. Vehicle detection challenge. ftp: A//motinas. elec. qmul. Ac. uk/pub/iLids, 2007.
13. A. Jazayeri, H. Cai, J. Y. Zheng, and M. Tuceryan. Vehicle detection and tracking in car video based on motion model. Intelligent Transportation Systems, IEEE Transactions on, 12 (2): A583-595, June 2011.
14. J. T. Lee, M. S. Ryoo, M. Riley, and J. K. Aggarwal. Realtime illegal parking detection in outdoor environments using 1-d transformation. IEEE Trans. Cir. And Sys. for Video Technol., 19 (7): A1014-1024, July 2009.
15. L. Maddalena and A. Petrosino. Stopped object detection by learning foreground model in videos. IEEE transactions on neural networks and learning systems, 24 (5): A723-735, 2013.
16. B. Morris and M. Trivedi. A survey of vision-based trajectory learning and analysis for surveillance. Circuits and Systems for Video Technology, IEEE Transactions on, 18 (8): A1114-1127, Aug 2008.
17. B. Morris and M. Trivedi. Trajectory learning for activity understanding: AUnsupervised, multilevel, and long-term adaptive approach. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 33 (11): A2287-2301, Nov 2011.
18. J. Pan, Q. Fan, and S. Pankanti. Robust abandoned object detection using region-level analysis. In Image Processing (ICIP), 2011 18th IEEE International Conference on, pages 3597-3600. IEEE, 2011.
19. PETS. Pets: APerformance evaluation of tracking and surveillance. http: A//www. cvg. reading. Ac. uk/slides/pets. html, 2015.
20. F. Porikli, Y. Ivanov, and T. Haga. Robust abandoned object detection using dual foregrounds. EURASIP Journal on Advances in Signal Processing, 2008: A30, 2008.
21. A. Singh, S. Sawan, M. Hanmandlu, V. K. Madasu, and B. C. Lovell. An abandoned object detection system based on dual background segmentation. In IEEE AVSS, pages 352-357. IEEE, 2009.
22. S. Sivaraman and M. Trivedi. Integrated lane and vehicle detection, localization, and tracking: AA synergistic approach. Intelligent Transportation Systems, IEEE Transactions on, 14 (2): A906-917, June 2013.
23. H. Smitha and V. Palanisamy. Detection of stationary foreground objects in region of interest from traffic video sequences. International Journal of Computer Science Issues, 9 (2): A194-199, 2012.
24. Y. Tian, R. S. Feris, H. Liu, A. Hampapur, and M.-T. Sun. Robust detection of abandoned and removed objects in complex surveillance videos. Systems, Man, and Cybernetics, Part C: AApplications and Reviews, IEEE Transactions on, 41 (5): A565-576, 2011.