The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Face pose discrimination using support vector machines (SVM)
Abstract
This paper describes an approach for the problem of face pose discrimination using support vector machines (SVM). Face pose discrimination means that one can label the face image as one of several known poses. Face images are drawn from the standard FERET database. The training set consists of 150 images equally distributed among frontal, approximately 33.75/spl deg/ rotated left and right poses, respectively, and the test set consists of 450 images again equally distributed among the three different types of poses. SVM achieved perfect accuracy-100%-discriminating between the three possible face poses on unseen test data, using either polynomials of degree 3 or radial basis functions (RBF) as kernel approximation functions.
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Citations
Cites
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
Cited by
FloatBoost learning and statistical face detection
Li, S. Z., & Zhang, Z. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.68 · Cited by 525
Statistical Learning of Multi-view Face Detection
Li, S. Z., Zhu, L., Zhang, Z., Blake, A., Zhang, H., & Shum, H. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-47979-1_5 · Cited by 398
Metadata
- Authors
- Huang, J., Shao, X., & Wechsler, H.
- Venue
- Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170)
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-27
- Volume
- 1
- Pages
- 154-156
- ISSN
- 1041-3278 (ISSN-L)
- OpenAlex
- W2131227845
- Cited by
- 187
- References
- 1
- FWCI
- 7.44
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Huang, J., Shao, X., & Wechsler, H. (2002). Face pose discrimination using support vector machines (SVM). Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170). https://doi.org/10.1109/icpr.1998.711102
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