Review: Sparse Representation for Face Recognition Application

Minakshi S. Nagmote; Dr.Milind M. Mushrif

doi:https://doi.org/10.14445/22315381/IJETT-V4I5P90

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Volume 4 | Issue 5 | Year 2013 | Article Id. IJETT-V4I5P90 | DOI : https://doi.org/10.14445/22315381/IJETT-V4I5P90

Review: Sparse Representation for Face Recognition Application

Minakshi S. Nagmote , Dr.Milind M. Mushrif

Citation :

Minakshi S. Nagmote , Dr.Milind M. Mushrif, "Review: Sparse Representation for Face Recognition Application," International Journal of Engineering Trends and Technology (IJETT), vol. 4, no. 5, pp. 1772-1775, 2013. Crossref, https://doi.org/10.14445/22315381/IJETT-V4I5P90

Abstract

In recent years, signal processing has come under pressure to accommodate the increasingly high - dimensional data generated by modern sensing systems. In many cases these high - dimensional signals contain relatively little information compared to their ambient dimensionality. Thus signals can often be well - approximated as a sparse linear combination of elements from a known basis or dictionary. Sparse models are exploited only after acquisition, typically for compression. In this paper we discuss how face detec tion problem is solved using sparse representation with the touch of compressive sensing theory. We consider sparsity based classification here.

Keywords

Face Recognition, Sparse Representation, l 1 - minimization

References

[1] A. Samal and P.A. Iyengar, “Automatic recognition and analysis of human faces and facial expressions: A survey,” Pattern recognition , vol. 25, no. 1, pp. 65 – 77, 1992.
[2] R. Chellappa, C.L. Wilson, S. Sirohey, et al., “Human and machine recognition of faces: A survey,” Proceedings of the IEEE , vol. 83, no. 5, pp. 705 – 740, 1995.
[3] B. Fasel and J. Luettin, “Automatic facial expression analysis: a survey,” Pattern Recognition , vol. 36, no.1, pp. 259 – 275, 2003.
[4] J. Wright, A. Yang, A. Ganesh, S. Sastry, and Y. Ma, “Robust face recognition via sparse representation,” PAMI, vol. 31, no. 2, pp. 210 – 227, 2009.
[5] A. Wagner, J. Wright, A. Ganesh, Z. Zhou, and Y. Ma, “Toward a practical face recognition: Robust pose and illumination via sparse representation,” in CVPR, 2009.
[6] John Wright, Student Member, IEEE, Allen Y. Yang, Member, IEEE, Arvind Ganesh, Student Member, IEEE, S. Shankar Sastry, Fellow, IEEE, and Yi Ma, Senior Member, IEEE, ‘Robust Face Recognition via Sparse Representation’, IEEE trans. On pattern analysis and machine intelligence vol 31 no 2 feb 2009.
[7]John Wright, Allen Yang, and Arvind Ganesh, ’Robust Face Recogniti on via Sparse Representation’, IEEE Trans, 2008.
[8] E. Cande`s, “Compressive Sampling,” Proc. Int’l Congress of Mathematicians, 2006.
[9]A. Bruckstain , D. Donoho, and M. Elad. From sparse solutions of systems of equations to sparse modelling of signal s and image SIAM Review, 2007.
[10]Allen Y Yang, Arvind Ganesh , S. Shankar Sastry,and Yi Ma, Fast l1 - Minimization Algorithms and An application in Robust Face Recognition Review.