Abstract
Face recognition in uncontrolled environments, such as large pose variations, and extreme ambient illumination and expressions is a challenging task for traditional face recognition methods. Some recent works show that context information such as clothes and social relationships is very important for solving the problem. Furthermore, sparse representation-based method is very robust for face occlusion and pixel contamination. In this paper, the authors propose a sparse learning framework for face recognition with social context. First, sparse representation based dimensionality reduction method is used to find the low dimension representation of the face images. Second, sparse representation based classification is utilized to classify test face images as known label and unknown label. Third, for test images classified as unknown label, social context descriptor is constructed according to co-existence information. Finally, based on social context descriptor and the low dimension representation of the test images classified as unknown label, sparse representation based clustering is adopted to perform face recognition.
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References
Singla, P., Kautz, H., Luo, J., Gallagher, A.: Discovery of Social Relationships in Consumer Photo Collections using Markov Logic. In: 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 1-3, pp. 735–741 (2008)
Stone, Z., Zickler, T., Darrell, T.: Toward Large-Scale Face Recognition Using Social Network Context. Proceedings of the IEEE 98, 1408–1415 (2010)
Lin, D., Kapoor, A., Hua, G., Baker, S.: Joint People, Event, and Location Recognition in Personal Photo Collections Using Cross-Domain Context. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part I. LNCS, vol. 6311, pp. 243–256. Springer, Heidelberg (2010)
Gallagher, A.C., Chen, T.: Using Context to Recognize People in Consumer Images. IPSJ Transactions on Computer Vision and Applications 1, 115–126 (2009)
Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust Face Recognition via Sparse Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 31, 210–227 (2009)
Hoyer, P.O.: Non-negative matrix factorization with sparseness constraints. Journal of Machine Learning Research 5, 1457–1469 (2004)
Pu, X., Yi, Z., Zheng, Z., Zhou, W., Ye, M.: Face recognition using fisher non-negative matrix factorization with sparseness constraints. In: Wang, J., Liao, X.-F., Yi, Z. (eds.) ISNN 2005. LNCS, vol. 3497, pp. 112–117. Springer, Heidelberg (2005)
Cheng, B., Yang, J.C., Yan, S.C., Fu, Y., Huang, T.S.: Learning With l(1)-Graph for Image Analysis. IEEE Transactions on Image Processing 19, 858–866 (2010)
Cai, D., He, X., Han, J.: Spectral regression: A unified approach for sparse subspace learning. Presented at the International Conference on Data Mining (ICDM 2007), Omaha, NE (2007)
Zou, H., Hastie, T., Tibshirani, R.: Sparse principal component analysis. Journal of Computational and Graphical Statistics 15, 265–286 (2006)
Zass, R., Shashua, A.: Nonnegative sparse PCA. Advances in Neural Information Processing Systems 19, 1561 (2007)
Qiao, L.S., Chen, S.C., Tan, X.Y.: Sparsity preserving projections with applications to face recognition. Pattern Recognition 43, 331–341 (2010)
Zhang, L., Yang, M., Feng, Z., Zhang, D.: On the Dimensionality Reduction for Sparse Representation based Face Recognition. In: 2010 International Conference on Pattern Recognition (2010)
Yang, J., Chu, D.: Sparse Representation Classifier Steered Discriminative Projection. In: 2010 International Conference on Pattern Recognition (2010)
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Gui, J., Mi, JX., Lei, YK., Wang, HQ. (2013). Sparse Learning for Face Recognition with Social Context. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_103
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DOI: https://doi.org/10.1007/978-3-642-42057-3_103
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