The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Image analysis and rule-based reasoning for a traffic monitoring system
Open accessAbstract
The paper presents an approach for detecting vehicles in urban traffic scenes by means of rule-based reasoning on visual data. The strength of the approach is its formal separation between the low-level image processing modules and the high-level module, which provides a general-purpose knowledge-based framework for tracking vehicles in the scene. The image-processing modules extract visual data from the scene by spatio-temporal analysis during daytime, and by morphological analysis of headlights at night. The high-level module is designed as a forward chaining production rule system, working on symbolic data, i.e., vehicles and their attributes (area, pattern, direction, and others) and exploiting a set of heuristic rules tuned to urban traffic conditions. The synergy between the artificial intelligence techniques of the high-level and the low-level image analysis techniques provides the system with flexibility and robustness.
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Citations
Cites
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Moving target classification and tracking from real-time video
Lipton, A. J., Fujiyoshi, H., & Patil, R. S. (2002) · Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201) · doi:10.1109/acv.1998.732851 · Cited by 1,108
Robust multiple car tracking with occlusion reasoning
Koller, D., Weber, J., & Malik, J. (1994) · Lecture Notes in Computer Science · doi:10.1007/3-540-57956-7_22 · Cited by 509
Vehicle detection video through image processing: the Autoscope system
Michalopoulos, P. G. (1991) · IEEE Transactions on Vehicular Technology · doi:10.1109/25.69968 · Cited by 275
A shadow handler in a video-based real-time traffic monitoring system
Kilger, M. (2003) · Proceedings · doi:10.1109/acv.1992.240332 · Cited by 154
Video-based traffic monitoring
Kilger, M. (1992) · Cited by 99
Cited by
Automatic Traffic Surveillance System for Vehicle Tracking and Classification
Hsieh, J.-W., Yu, S.-H., Chen, Y.-S., & Hu, W.-F. (2006) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2006.874722 · Cited by 423
Hierarchical and Networked Vehicle Surveillance in ITS: A Survey
Tian, B., Morris, B. T., Tang, M., Liu, Y., Yao, Y., Gou, C., Shen, D., & Tang, S. (2017) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2016.2552778 · Cited by 160
Cao, X., Wu, C., Yan, P., & Li, X. (2011) · 2011 18th IEEE International Conference on Image Processing · doi:10.1109/icip.2011.6116132 · Cited by 151
Urban Traffic Density Estimation Based on Ultrahigh-Resolution UAV Video and Deep Neural Network
Zhu, J., Sun, K., Jia, S., Li, Q., Hou, X., Lin, W., Liu, B., & Qiu, G. (2018) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2018.2879368 · Cited by 127
Video processing techniques for traffic flow monitoring: A survey
Tian, B., Yao, Q., Gu, Y., Wang, K., & Li, Y. (2011) · 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2011.6083125 · Cited by 106
Metadata
- Authors
- Cucchiara, R., Piccardi, M., & Mello, P.
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2000-06
- Volume
- 1
- Issue
- 2
- Pages
- 119-130
- ISSN
- 1524-9050 (ISSN-L)
- OpenAlex
- W2124798378
- Cited by
- 398
- References
- 12
- FWCI
- 10.96
- Type
- journal article
- Language
- en
- Open access
- green
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- Cucchiara, R., Piccardi, M., & Mello, P. (2000). Image analysis and rule-based reasoning for a traffic monitoring system. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/6979.880969
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
