The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Fast ℓ1-minimization algorithms and an application in robust face recognition: A review
Abstract
We provide a comprehensive review of five representative ℓ1-minimization methods, i.e., gradient projection, homotopy, iterative shrinkage-thresholding, proximal gradient, and augmented Lagrange multiplier. The repository is intended to fill in a gap in the existing literature to systematically benchmark the performance of these algorithms using a consistent experimental setting. The experiment will be focused on the application of face recognition, where a sparse representation framework has recently been developed to recover human identities from facial images that may be affected by illumination change, occlusion, and facial disguise. The paper also provides useful guidelines to practitioners working in similar fields.
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Cites
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
Beck, A., & Teboulle, M. (2009) · SIAM Journal on Imaging Sciences · doi:10.1137/080716542 · Cited by 11,952
Bertsekas, D. P. (1997) · Journal of the Operational Research Society · doi:10.1038/sj.jors.2600425 · Cited by 11,726
Robust Face Recognition via Sparse Representation
Wright, J., Yang, A. Y., Ganesh, A., Sastry, S. S., & Ma, Y. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.79 · Cited by 9,388
Self-citationEfron, B., Hastie, T., Johnstone, I., & Tibshirani, R. (2004) · The Annals of Statistics · doi:10.1214/009053604000000067 · Cited by 9,357
Stable signal recovery from incomplete and inaccurate measurements
Candès, E. J., Romberg, J. K., & Tao, T. (2006) · Communications on Pure and Applied Mathematics · doi:10.1002/cpa.20124 · Cited by 7,036
Atomic Decomposition by Basis Pursuit
Chen, S. S., Donoho, D. L., & Saunders, M. A. (2001) · SIAM Review · doi:10.1137/s003614450037906x · Cited by 5,085
Figueiredo, M. A. T., Nowak, R. D., & Wright, S. J. (2007) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2007.910281 · Cited by 3,524
Signal Recovery by Proximal Forward-Backward Splitting
Combettes, P. L., & Wajs, V. R. (2005) · Multiscale Modeling & Simulation · doi:10.1137/050626090 · Cited by 2,678
A method for solving the convex programming problem with convergence rate O(1/k^2)
Nesterov, Y. E. (1983) · Доклады Академии наук · Cited by 2,662
From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
Bruckstein, A. M., Donoho, D. L., & Elad, M. (2009) · SIAM Review · doi:10.1137/060657704 · Cited by 2,183
Cited by
Real time robust L1 tracker using accelerated proximal gradient approach
Bao, C., Wu, Y., Ling, H., & Ji, H. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247881 · Cited by 835
Fast $\ell_{1}$-Minimization Algorithms for Robust Face Recognition
Yang, A. Y., Zhou, Z., Balasubramanian, A. G., Sastry, S. S., & Ma, Y. (2013) · IEEE Transactions on Image Processing · doi:10.1109/tip.2013.2262292 · Cited by 341
Self-citationA Nonlocal Weighted Joint Sparse Representation Classification Method for Hyperspectral Imagery
Zhang, H., Li, J., Huang, Y., & Zhang, L. (2014) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2013.2264720 · Cited by 284
Metadata
- Authors
- Yang, A. Y., Sastry, S. S., Ganesh, A., & Ma, Y.
- Venue
- 2010 IEEE International Conference on Image Processing
- Publisher
- IEEE
- Published
- 2010-09
- Pages
- 1849-1852
- ISSN
- 1522-4880 (ISSN-L)
- OpenAlex
- W1983008863
- Cited by
- 414
- References
- 19
- FWCI
- 69.58
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Yang, A. Y., Sastry, S. S., Ganesh, A., & Ma, Y. (2010). Fast ℓ1-minimization algorithms and an application in robust face recognition: A review. 2010 IEEE International Conference on Image Processing. https://doi.org/10.1109/icip.2010.5651522
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
