A Machine–Vision System to Detect Unusual Activities Online at Vehicular Intersections
Un Sistema de Visión por Computadora para Detectar en Línea Actividades Inusuales en Intersecciones Vehiculares
Sandra Luz Canchola Magdaleno, Joaquín Salas Rodríguez, Hugo Jiménez Hernández, José Joel González Barbosa and Juan B. Hurtado Ramos
CICATA Qro. IPN. scanchola@ipn.mx, salas@ieee.org, hugojh@gmail.com, jgonzalezba@ipn.mx, jbautistah@ipn.mx
]]> Article received on January 04, 2008
Abstract
In this article, we present a real–time machine–vision system to detect vehicles running on red light or performing forbidden turns at crossroads. The system operates during daytime by receiving video streams from two different sources. One of them is a camera viewing the crossroads to detect unusual activity, while a second camera watches the semaphore to keep synchrony with the traffic controller. The system performance and reliability have been tested on a real vehicular intersection during extended periods of time.
Keywords: Machine vision, real–time systems, unusual activity detection, automatic surveillance.
Resumen
En este artículo, presentamos un sistema de visión por computadora para detectar, en tiempo real, vehículos pasándose el alto o realizando vueltas prohibidas en cruceros viales. El sistema opera durante el día recibiendo secuencias de video de dos diferentes fuentes. Una de ellas observa el crucero para detectar actividad inusual, mientras que la segunda monitorea el semáforo para mantener la sincronía con el controlar de tráfico. El desempeño y confiabilidad del sistema han sido probados en una intersección vehicular real durante períodos de tiempo que abarcan días.
Palabras clave: Visión por computadora, sistemas en tiempo real, detección de actividad inusual, vigilancia automática.
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References
1. Angel, A., M. Hickman, P. Mirchandani, and D. Chandnani. "Methods of Analyzing Traffic Imagery Collected from Aerial Platforms." IEEE Transactions on Intelligent Transportation Systems 4, no. 2 (2003): 99 –107. [ Links ]
2. Atev, S., H. Arumugam, O. Masoud, R. Janardan, and N. P. Papanikolopoulos. "A Vision–Based Approach to Collision Prediction at Traffic Intersections." IEEE Transactions on Intelligent Transportation Systems 6, no. 4 (2005): 416–423. [ Links ]
3. Beymer, D., P. McLauchlan, B. Coifman, and J. Malik. "A Real Time Computer Vision System for Measuring Traffic Parameters." Computer Vision and Pattern Recognition. San Juan, Puerto Rico: IEEE Computer Society, 1997. 495–501. [ Links ]
4. Boiman, O., and M. Irani. "Detecting Irregularities in Images and in Video." International Conference on Computer Vision. Beijing, China: IEEE Computer Society, 2005. 462–469. [ Links ]
5. Brand, M., N. Oliver, and A. Pentland. "Coupled Hidden Markov Models for Complex Action Recognition." Computer Vision and Pattern Recognition. Los Alamitos, CA, USA: IEEE Computer Society, 1997. 994–999. [ Links ]
6. Chan, M. T., A. Hoogs, J. Schmiederer, and M. Petersen. "Detecting Rare Events in Video using Semantic Primitives with HMM." International Conference on Pattern Recognition. Cambridge, UK: IEEE Computer Society, 2004. 150–154. [ Links ]
7. Cucchiara, R., M. Piccardi, and P. Mello. "Image Analysis and Rule–Based Reasoning for a Traffic Monitoring System." Transactions on Intelligent Transportation Systems. Beijing, China: IEEE Computer Society, 2000. 119 – 130. [ Links ]
8. Dailey, D. J., F. W. Cathey, and S. Pumrin. "An Algorithm to Estimate Mean Traffic Speed using Uncalibrated Cameras." IEEE Transactions on Intelligent Transportation Systems 1, no. 2 (2000): 119–130. [ Links ]
9. Dee, H., and D. Hogg. "Detecting Inexplicable Behaviour." British Machine Vision Conference. Kingston, UK, 2004. 477–486. [ Links ]
10. Duda, R.O., P.E. Hart, and D.G. Stork. Pattern Classification. Wiley, 2001. [ Links ]
11. Fuerstenberg, K. C., and B. Roessler. "Advanced Intersection Safety – The EC project INTERSAFE." Intelligent Vehicles Symposium. 2006. 89 – 93. [ Links ]
12. Gutchess, D., M. Trajkovics, E. Cohen–Solal, D. Lyons, and A. K. Jain. "A Background Model Initialization Algorithm for Video Surveillance." International Conference on Computer Vision. Vancouver, Canada: IEEE Computer Society, 2001. 733 – 740. [ Links ]
13. Johnson, N., and D. C. Hogg. "Learning the Distribution of Object Trajectories for Event Recognition." Image and Vision Computing 14, no. 8 (1996): 609–615. [ Links ]
14. Jung, Y.K., K.W. Lee, and Y.S. Ho. "Content–Based Event Retrieval using Semantic Scene Interpretation for Automated Traffic Surveillance." IEEE Transactions on Intelligent Transportation Systems 2, no. 3 (2001): 151 – 163. [ Links ]
15. Kamijo, S., Y. Matsushita, K. Ikeuchi, and M. Sakauchi. "Traffic Monitoring and Accident Detection at Intersections." IEEE Transactions on Intelligent Transportation Systems 1, no. 2 (2000): 108–118. [ Links ]
16. Kato, J., T. Watanabe, S. Joga, J. Rittscher, and A. Blake. "An HMM–Based Segmentation Method for Traffic Monitoring Movies." IEEE Pattern Analysis and Machine Intelligence 24, no. 9 (2002): 1291 – 1296. [ Links ]
17. Kato, J., T. Watanabe, S. Joga, Y. Liu, and H. Hase. "An HMM/MRF–Based Stochastic Framework for Robust Vehicle Tracking." IEEE Transactions on Intelligent Transportation Systems 5, no. 3 (2004): 142 – 154. [ Links ]
18. Lucas, B. D., and T. Kanade. "An Iterative Image Registration Technique with an Application to Stereo Vision." Image Understanding Workshop. Washington, DC, USA: Defense Advanced Research Projects Agency, 1981. 121–130. [ Links ]
19. Medioni, G. G., I. Cohen, F. Bremond, S. Hongeng, and R. Nevatia. "Event Detection and Analysis from Video Streams." IEEE Pattern Analysis and Machine Intelligence 23, no. 8 (2001): 873–889. [ Links ]
20. Otsu, N. "A Threshold Selection Method from Gray Level Histograms." IEEE Transactions on Systems, Man and Cybernetics VIII (1978): 62–66. [ Links ]
21. Salas, J., H. Jiménez, J. González, J. Hurtado, and S. Canchola. "A Double Layer Background Model to Detect Unusual Events." Edited by Springer Berlin / Heidelberg. Lecture Notes in Computer Science 4678 (2007): 406–416. [ Links ]
22. Schoepflin, T., and D. Dailey. "Dynamic Camera Calibration of Roadside Traffic Management Cameras for Vehicle Speed Estimation." IEEE Transactions on Intelligent Transportation Systems 4, no. 2 (2003): 90 – 98. [ Links ]
23. Stauffer, C., and W. E. L. Grimson. "Adaptive Background Mixture Models for Real–Time Tracking." Computer Vision and Pattern Recognition. Fort Colins, CO., USA: IEEE Computer Society, 1999. 246–252. [ Links ]
24. Stauffer, C., and W. E. L. Grimson. "Learning Patterns of Activity Using Real–Time Tracking." IEEE Pattern Analysis and Machine Intelligence 22, no. 8 (2000): 747–757. [ Links ]
25. Tai, J.C., and K.T. Song. "Background Segmentation and its Application to Traffic Monitoring using Modified Histogram." Int. Conf. on Networking, Sensing and Control. Taipei, Taiwan, 2004. 13 – 18. [ Links ]
26. Tomasi, C., and J. Shi. "Good Features to Track." Computer Vision and Pattern Recognition . Seattle, Washington, USA: IEEE Computer Society, 1994. 593–600. [ Links ]
27. Veeraraghavan, H., O. Masoud, and N. P. Papanikolopoulos. "Computer Vision Algorithms for Intersection Monitoring." IEEE Transactions on Intelligent Transportation Systems 4, no. 2 (2003): 78–89. [ Links ]
28. Xiang, T., and S. Gong. "Video Behaviour Profiling and Abnormality Detection without Manual Labelling." International Conference on Computer Vision. Beijing, China: IEEE Computer Society, 2005. 1238–1245. [ Links ]
29. Yamada, K., and M. Soga. "A Compact Integrated Visual Motion Sensor for its Applications." IEEE Transactions on Intelligent Transportation Systems 4, no. 1 (2003): 35 – 42. [ Links ]
30. Zhong, H., J. Shi, and M. Visontai. "Detecting Unusual Activity in Video." Computer Vision and Pattern Recognition . Washington, DC., USA: IEEE Computer Society, 2004. 819–826. [ Links ] ]]>