The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Pedestrian detection using wavelet templates
Abstract
This paper presents a trainable object detection architecture that is applied to detecting people in static images of cluttered scenes. This problem poses several challenges. People are highly non-rigid objects with a high degree of variability in size, shape, color, and texture. Unlike previous approaches, this system learns from examples and does not rely on any a priori (hand-crafted) models or on motion. The detection technique is based on the novel idea of the wavelet template that defines the shape of an object in terms of a subset of the wavelet coefficients of the image. It is invariant to changes in color and texture and can be used to robustly define a rich and complex class of objects such as people. We show how the invariant properties and computational efficiency of the wavelet template make it an effective tool for object detection.
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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
Original approach for the localisation of objects in images
Vaillant, R. (1994) · IEE Proceedings - Vision, Image, and Signal Processing · doi:10.1049/ip-vis:19941301 · Cited by 280
Cited by
Shape matching and object recognition using shape contexts
Belongie, S., Malik, J., & Puzicha, J. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.993558 · Cited by 6,306
(1998) · Cited by 2,679
Poselets: Body part detectors trained using 3D human pose annotations
Bourdev, L., & Malik, J. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459303 · Cited by 961
Guan, D., Cao, Y., Yang, J., Cao, Y., & Yang, M. Y. (2019) · Information Fusion · doi:10.1016/j.inffus.2018.11.017 · Cited by 342
Carneiro, G., Georgescu, B., Good, S., & Comaniciu, D. (2008) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.928917 · Cited by 205
Metadata
- Authors
- Oren, M., Papageorgiou, C., Sinha, P., Osuna, E., & Poggio, T.
- Venue
- Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-22
- Pages
- 193-199
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2104671481
- Cited by
- 695
- References
- 2
- FWCI
- 27.15
- Type
- conference paper
- Language
- en
- Open access
- closed
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