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Detecting and tracking moving objects for video surveillance
Abstract
We address the problem of detection and tracking of moving objects in a video stream obtained from a moving airborne platform. The proposed method relies on a graph representation of moving objects which allows to derive and maintain a dynamic template of each moving object by enforcing their temporal coherence. This inferred template along with the graph representation used in our approach allows us to characterize objects trajectories as an optimal path in a graph. The proposed tracker allows to deal with partial occlusions, stop and go motion in very challenging situations. We demonstrate results on a number of different real sequences. We then define an evaluation methodology to quantify our results and show how tracking overcome detection errors.
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Cited by
Detecting moving shadows: algorithms and evaluation
Prati, A., Mikic, I., Trivedi, M. M., & Cucchiara, R. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1206520 · Cited by 760
Learning What to Learn for Video Object Segmentation
Bhat, G., Lawin, F. J., Danelljan, M., Robinson, A., Felsberg, M., Van Gool, L., & Timofte, R. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58536-5_46 · Cited by 160
Learning Fast and Robust Target Models for Video Object Segmentation
Robinson, A., Jaremo Lawin, F., Danelljan, M., Khan, F. S., & Felsberg, M. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00743 · Cited by 158
Metadata
- Authors
- Cohen, I., & Medioni, G.
- Venue
- Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)
- Publisher
- IEEE Comput. Soc
- Published
- 2003-01-20
- Pages
- 319-325
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2115606256
- Cited by
- 212
- References
- 0
- FWCI
- 12.83
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Detecting and tracking moving objects for video surveillance. https://app.cochat.ai/papers/10.1109/cvpr.1999.784651
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- Cohen, I., & Medioni, G. (2003). Detecting and tracking moving objects for video surveillance. Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149). https://doi.org/10.1109/cvpr.1999.784651
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