Open Access
Subscription Access
Face Recognition Using a Hybrid SVM–LBP Approach and the Indian Movie Face Database
Local binary patterns (LBP) are an effective texture descriptor for face recognition. In this work, a LBP based hybrid system for face recognition is proposed.Thus, the dimensionality of LBP histograms is reduced by using principal component analysis and the classification is performed with support vector machines. The experiments were completed using the challenging Indian Movie Face Database and show that our method achieves high recognition rates while reducing 95% the dimensions of the original LBP histograms. Moreover, our algorithm is compared against some state-of-the-art approaches. The results indicate that our method outperforms other approaches, with accurate face recognition results.
Keywords
Face Recognition, Hybrid Methods, Local Binary Patterns, Support Vector Machines.
User
Font Size
Information
- Ojala, T., Pietikäinen, M. and Harwood, D., A comparative study of texture measures with classification based on featured distributions. Pattern Recogn., 1996, 29, 51–59.
- Setty, S. et al., Indian movie face database: a benchmark for face recognition under wide variations. In Proceedings of the 2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), 2013.
- Beham, M. P., Roomi, S. and Kapileshwaran, V., Robust face recognition using automatic pose clustering and pose estimation. In Proceedings of the 2013 Fifth International Conference on Advanced Computing (ICoAC), 2013.
- Kumar, V., Namboodiri, A.M. and Jawahar, C.V., Face recognition in videos by label propagation. In Proceedings of the 22nd International Conference on Pattern Recognition (ICPR), 2014.
- Ahonen, T., Hadid, A. and Pietikäinen, M., Face recognition with local binary patterns. In Proceedings of the 8th European Conference on Computer Vision, ECCV 2004, Prague, Czech Republic, 2004, pp. 469–481.
- Zhang, W., Shan, S., Gao, W., Chen, X. and Zhang, H., Local Gabor binary pattern histogram sequence (lgbphs): a novel non-statistical model for face representation and recognition. In Proceedings of the 10th International Conference on Computer Vision, 2005.
- Maturana, D., Mery, D. and Soto, A., Learning discriminative local binary patterns for face recognition. In Proceedings of the IEEE International Conf. on Automatic Face & Gesture Recognition, 2011.
- Yang, M., Zhang, L., Shiu, S. K. and Zhang, D., Robust kernel representation with statistical local features for face recognition. IEEE T. Neural Network., 2013, 24, 900–912.
- Vu, N. S. and Caplier, A., Enhanced patterns of oriented edge magnitudes for face recognition and image matching. IEEE T. Image Process., 2012, 21, 1352–1365.
Abstract Views: 310
PDF Views: 104