The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Moving target classification and tracking from real-time video
Abstract
This paper describes an end-to-end method for extracting moving targets from a real-time video stream, classifying them into predefined categories according to image-based properties, and then robustly tracking them. Moving targets are detected using the pixel wise difference between consecutive image frames. A classification metric is applied these targets with a temporal consistency constraint to classify them into three categories: human, vehicle or background clutter. Once classified targets are tracked by a combination of temporal differencing and template matching. The resulting system robustly identifies targets of interest, rejects background clutter and continually tracks over large distances and periods of time despite occlusions, appearance changes and cessation of target motion.
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Citations
Cites
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
Cited by
Comaniciu, D., Ramesh, V., & Meer, P. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1195991 · Cited by 4,560
W/sup 4/: real-time surveillance of people and their activities
Haritaoglu, I., Harwood, D., & Davis, L. S. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.868683 · Cited by 2,523
Statistical Modeling of Complex Backgrounds for Foreground Object Detection
Li, L., Huang, W., Gu, I. Y.-H., & Tian, Q. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2004.836169 · Cited by 991
A Survey of Visual Sensor Networks
Soro, S., & Heinzelman, W. (2009) · Advances in Multimedia · doi:10.1155/2009/640386 · Cited by 445
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
Metadata
- Authors
- Lipton, A. J., Fujiyoshi, H., & Patil, R. S.
- Venue
- Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201)
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-27
- Pages
- 8-14
- ISSN
- 1550-5790 (ISSN-L)
- OpenAlex
- W1687797484
- Cited by
- 1,108
- References
- 1
- FWCI
- 35.19
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Lipton, A. J., Fujiyoshi, H., & Patil, R. S. (2002). Moving target classification and tracking from real-time video. Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201). https://doi.org/10.1109/acv.1998.732851
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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.
