The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Rotation Invariant Neural Network-Based Face Detection
Abstract
In this paper, we present a neural network-based face detection system. Unlike similar systems which are limited to detecting upright, frontal faces, this system detects faces at any degree of rotation in the image plane. The system employs multiple networks; a "router" network first processes each input window to determine its orientation and then uses this information to prepare the window for one or more "detector" networks. We present the training methods for both types of networks. We also perform sensitivity analysis on the networks, and present empirical results on a large test set. Finally, we present preliminary results for detecting faces rotated out of the image plane, such as profiles and semi-profiles. 1. Introduction In our observations of face detector demonstrations, we have found that users expect faces to be detected at any angle, as shown in Figure 1. In this paper, we present a neural network-based algorithm to detect faces in gray-scale images. Unlike similar pre...
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Cites
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
Self-citationOriginal 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
From few to many: illumination cone models for face recognition under variable lighting and pose
Georghiades, A. S., Belhumeur, P. N., & Kriegman, D. J. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.927464 · Cited by 4,912
Detecting faces in images: a survey
Yang, M.-H., Kriegman, D. J., & Ahuja, N. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.982883 · Cited by 3,427
A convolutional neural network cascade for face detection
Li, H., Lin, Z., Shen, X., Brandt, J., & Hua, G. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7299170 · Cited by 1,390
Kostinger, M., Wohlhart, P., Roth, P. M., & Bischof, H. (2011) · 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops) · doi:10.1109/iccvw.2011.6130513 · Cited by 715
Orientation robust object detection in aerial images using deep convolutional neural network
Zhu, H., Chen, X., Dai, W., Fu, K., Ye, Q., & Jiao, J. (2015) · 2015 IEEE International Conference on Image Processing (ICIP) · doi:10.1109/icip.2015.7351502 · Cited by 483
Metadata
- Authors
- Rowley, H. A., Baluja, S., & Kanade, T.
- Venue
- Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231)
- Publisher
- IEEE Comput. Soc
- Published
- 2005-08-24
- Pages
- 963-963
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2154376992
- Cited by
- 470
- References
- 2
- FWCI
- 28.66
- Type
- conference paper
- Language
- en
- Open access
- closed
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- The paper
- Rowley, H. A., Baluja, S., & Kanade, T. (2005). Rotation Invariant Neural Network-Based Face Detection. Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231). https://doi.org/10.1109/cvpr.1998.698721
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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