The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Pedestrian Detection and Tracking With Night Vision
Abstract
This paper presents a method for pedestrian detection and tracking using a single night-vision video camera installed on the vehicle. To deal with the nonrigid nature of human appearance on the road, a two-step detection/tracking method is proposed. The detection phase is performed by a support vector machine (SVM) with size-normalized pedestrian candidates and the tracking phase is a combination of Kalman filter prediction and mean shift tracking. The detection phase is further strengthened by information obtained by a road-detection module that provides key information for pedestrian validation. Experimental comparisons (e.g., grayscale SVM recognition versus binary SVM recognition and entire-body detection versus upper-body detection) have been carried out to illustrate the feasibility of our approach.
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Citations
Cites
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
The Nature of Statistical Learning Theory
Vapnik, V. N. (2000) · Springer eBooks · doi:10.1007/978-1-4757-3264-1 · Cited by 10,696
An Introduction to the Kalman Filter
Welch, G., & Bishop, G. (1995) · CiteSeer X (The Pennsylvania State University) · Cited by 4,895
Mean shift, mode seeking, and clustering
Cheng, Y. (1995) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.400568 · Cited by 3,856
Real-time tracking of non-rigid objects using mean shift
Comaniciu, D., Ramesh, V., & Meer, P. (2002) · Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662) · doi:10.1109/cvpr.2000.854761 · Cited by 2,906
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
Training support vector machines: an application to face detection
Osuna, E., Freund, R., & Girosit, F. (2002) · Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1997.609310 · Cited by 2,486
Detecting Pedestrians Using Patterns of Motion and Appearance
Viola, P., Jones, M. J., & Snow, D. (2005) · International Journal of Computer Vision · doi:10.1007/s11263-005-6644-8 · Cited by 2,079
Detecting pedestrians using patterns of motion and appearance
Viola, Jones, & Snow (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238422 · Cited by 1,002
Example-based object detection in images by components
Mohan, A., Papageorgiou, C., & Poggio, T. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.917571 · Cited by 948
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
Thermal cameras and applications: A survey
Gade, R., & Moeslund, T. B. (2014) · Machine Vision and Applications · doi:10.1007/s00138-013-0570-5 · Cited by 780
Long-Term Occupancy Analysis Using Graph-Based Optimisation in Thermal Imagery
Gade, R., Jorgensen, A., & Moeslund, T. B. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2013.474 · Cited by 437
A Two-Stage Template Approach to Person Detection in Thermal Imagery
Davis, J. W., & Keck, M. A. (2005) · 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1 · doi:10.1109/acvmot.2005.14 · Cited by 320
Sakaridis, C., Dai, D., & Van Gool, L. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00747 · Cited by 281
Metadata
- Authors
- Xu, F., Liu, X., & Fujimura, K.
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2005-03
- Volume
- 6
- Issue
- 1
- Pages
- 63-71
- ISSN
- 1524-9050 (ISSN-L)
- OpenAlex
- W2133984628
- Cited by
- 386
- References
- 36
- FWCI
- 41.88
- Type
- journal article
- Language
- en
- Open access
- closed
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- Xu, F., Liu, X., & Fujimura, K. (2005). Pedestrian Detection and Tracking With Night Vision. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2004.838222
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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.
