The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Clustering of Vehicle Trajectories
Abstract
We present a method that is suitable for clustering of vehicle trajectories obtained by an automated vision system. We combine ideas from two spectral clustering methods and propose a trajectory-similarity measure based on the Hausdorff distance, with modifications to improve its robustness and account for the fact that trajectories are ordered collections of points. We compare the proposed method with two well-known trajectory-clustering methods on a few real-world data sets.
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Cites
Advances in Neural Information Processing Systems 14: Proceedings of the 2001 Conference
(2002) · The MIT Press eBooks · doi:10.7551/mitpress/1120.001.0001 · Cited by 8,890
On Spectral Clustering: Analysis and an algorithm
Ng, A. Y., Jordan, M. I., & Weiss, Y. (2001) · Cited by 8,159
Comparing images using the Hausdorff distance
Huttenlocher, D. P., Klanderman, G. A., & Rucklidge, W. J. (1993) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.232073 · Cited by 4,545
Learning patterns of activity using real-time tracking
Stauffer, C., & Grimson, W. E. L. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.868677 · Cited by 3,248
Self-Tuning Spectral Clustering
Zelnik‐Manor, L., & Perona, P. (2004) · CaltechAUTHORS (California Institute of Technology) · Cited by 1,942
Advances in Neural Information Processing Systems 18
Murray, I., Mackay, D., Zoubin Ghahramani, A., & Skilling, J. (2006) · Cited by 1,927
Comparing clusterings—an information based distance
Meilă, M. (2007) · Journal of Multivariate Analysis · doi:10.1016/j.jmva.2006.11.013 · Cited by 1,546
Discovering similar multidimensional trajectories
Vlachos, M., Kollios, G., & Gunopulos, D. (2003) · Proceedings 18th International Conference on Data Engineering · doi:10.1109/icde.2002.994784 · Cited by 1,468
A modified Hausdorff distance for object matching
Dubuisson, M.-P., & Jain, A. K. (2002) · Proceedings of 12th International Conference on Pattern Recognition · doi:10.1109/icpr.1994.576361 · Cited by 1,464
Robust and fast similarity search for moving object trajectories
Chen, L., Özsu, M. T., & Oria, V. (2005) · Proceedings of the 2005 ACM SIGMOD international conference on Management of data · doi:10.1145/1066157.1066213 · Cited by 1,336
Cited by
Data-Driven Intelligent Transportation Systems: A Survey
Zhang, J., Wang, F.-Y., Wang, K., Lin, W.-H., Xu, X., & Chen, C. (2011) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2011.2158001 · Cited by 1,817
A survey on motion prediction and risk assessment for intelligent vehicles
Lefèvre, S., Vasquez, D., & Laugier, C. (2014) · ROBOMECH Journal · doi:10.1186/s40648-014-0001-z · Cited by 1,112
Challenges Toward Wireless Communications for High-Speed Railway
Ai, B., Briso-Rodriguez, C., Cheng, X., Kurner, T., Zhong, Z.-D., Guan, K., He, R.-S., Xiong, L., Matolak, D. W., & Michelson, D. G. (2014) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2014.2310771 · Cited by 498
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
Modeling Quality of IoT Experience in Autonomous Vehicles
Minovski, D., Ahlund, C., & Mitra, K. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.2975418 · Cited by 59
Metadata
- Authors
- Atev, S., Miller, G., & Papanikolopoulos, N. P.
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2010-09
- Volume
- 11
- Issue
- 3
- Pages
- 647-657
- ISSN
- 1524-9050 (ISSN-L)
- OpenAlex
- W2155295407
- Cited by
- 257
- References
- 24
- FWCI
- 14.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Atev, S., Miller, G., & Papanikolopoulos, N. P. (2010). Clustering of Vehicle Trajectories. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2010.2048101
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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