The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Detecting pedestrians using patterns of motion and appearance
Abstract
This paper describes a pedestrian detection system that integrates image intensity information with motion information. We use a detection style algorithm that scans a detector over two consecutive frames of a video sequence. The detector is trained (using AdaBoost) to take advantage of both motion and appearance information to detect a walking person. Past approaches have built detectors based on appearance information, but ours is the first to combine both sources of information in a single detector. The implementation described runs at about 4 frames/second, detects pedestrians at very small scales (as small as 20/spl times/15 pixels), and has a very low false positive rate. Our approach builds on the detection work of Viola and Jones. Novel contributions of this paper include: i) development of a representation of image motion which is extremely efficient, and ii) implementation of a state of the art pedestrian detection system which operates on low resolution images under difficult conditions (such as rain and snow).
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Cites
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Neural network-based face detection
Rowley, H. A., Baluja, S., & Kanade, T. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.655647 · Cited by 3,554
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Cited by
Histograms of Oriented Gradients for Human Detection
Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584
One-shot learning of object categories
Fei-Fei, L., Fergus, R., & Perona, P. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.79 · Cited by 3,029
An HOG-LBP human detector with partial occlusion handling
Wang, X., Han, T. X., & Yan, S. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459207 · Cited by 1,727
Fast Human Detection Using a Cascade of Histograms of Oriented Gradients
Zhu, Q., Yeh, M.-C., Cheng, K.-T., & Avidan, S. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.119 · Cited by 1,399
Pedestrian detection: A benchmark
Dollar, P., Wojek, C., Schiele, B., & Perona, P. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206631 · Cited by 1,313
Metadata
- Authors
- Viola, Jones, & Snow
- Venue
- Proceedings Ninth IEEE International Conference on Computer Vision
- Publisher
- IEEE
- Published
- 2003
- Pages
- 734-741 vol.2
- OpenAlex
- W3151111735
- Cited by
- 1,002
- References
- 2
- FWCI
- 27.88
- Type
- conference paper
- Language
- en
- Open access
- closed
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