The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Floor Fields for Tracking in High Density Crowd Scenes
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Citations
Cites
Mean shift: a robust approach toward feature space analysis
Comaniciu, D., & Meer, P. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.1000236 · Cited by 11,305
Yilmaz, A., Javed, O., & Shah, M. (2006) · ACM Computing Surveys · doi:10.1145/1177352.1177355 · Cited by 4,792
Self-citationSimulation of pedestrian dynamics using a two-dimensional cellular automaton
Burstedde, C., Klauck, K., Schadschneider, A., & Zittartz, J. (2001) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/s0378-4371(01)00141-8 · Cited by 1,769
Kirchner, A., & Schadschneider, A. (2002) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/s0378-4371(02)00857-9 · Cited by 892
Kirchner, A., & Schadschneider, A. (n.d.) · RePEc: Research Papers in Economics · Cited by 777
A Lagrangian Particle Dynamics Approach for Crowd Flow Segmentation and Stability Analysis
Ali, S., & Shah, M. (2007) · 2007 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2007.382977 · Cited by 590
Self-citationUnsupervised Bayesian Detection of Independent Motion in Crowds
Brostow, G. J., & Cipolla, R. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06) · doi:10.1109/cvpr.2006.320 · Cited by 413
An MCMC-Based Particle Filter for Tracking Multiple Interacting Targets
Khan, Z., Balch, T., & Dellaert, F. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24673-2_23 · Cited by 367
Tracking multiple humans in crowded environment
Zhao, T., & Nevatia, R. (2004) · Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. · doi:10.1109/cvpr.2004.1315192 · Cited by 340
Bayesian human segmentation in crowded situations
Zhao, T., & Nevatia, R. (2003) · 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings. · doi:10.1109/cvpr.2003.1211503 · Cited by 294
Cited by
You'll never walk alone: Modeling social behavior for multi-target tracking
Pellegrini, S., Ess, A., Schindler, K., & van Gool, L. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459260 · Cited by 1,683
Kitani, K. M., Ziebart, B. D., Bagnell, J. A., & Hebert, M. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33765-9_15 · Cited by 701
A survey of video datasets for human action and activity recognition
Chaquet, J. M., Carmona, E. J., & Fernández-Caballero, A. (2013) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2013.01.013 · Cited by 455
Crowd Analysis Using Computer Vision Techniques
Silveira Jacques Junior, J., Musse, S., & Jung, C. (2010) · IEEE Signal Processing Magazine · doi:10.1109/msp.2010.937394 · Cited by 343
Object Detection and Tracking for Autonomous Navigation in Dynamic Environments
Ess, A., Schindler, K., Leibe, B., & Van Gool, L. (2010) · The International Journal of Robotics Research · doi:10.1177/0278364910365417 · Cited by 191
Metadata
- Authors
- Ali, S., & Shah, M.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2008
- Volume
- 5303
- Pages
- 1-14
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1482815597
- Cited by
- 388
- References
- 13
- FWCI
- 22.17
- Type
- conference paper
- Language
- en
- Open access
- bronze
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: Floor Fields for Tracking in High Density Crowd Scenes. https://app.cochat.ai/papers/10.1007/978-3-540-88688-4_1
- The paper
- Ali, S., & Shah, M. (2008). Floor Fields for Tracking in High Density Crowd Scenes. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-540-88688-4_1
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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.
