Sparse representation and least squares-based classification in face recognition

Sparse representation and least squares-based classification in face recognition. Iliadis, M., Spinoulas, L., Berahas, A. S., Wang, H., & Katsaggelos, A. K. In 2014 22nd European Signal Processing Conference (EUSIPCO), pages 526-530, Sep., 2014.

Paper abstract bibtex

In this paper we present a novel approach to face recognition. We propose an adaptation and extension to the state-of-the-art methods in face recognition, such as sparse representation-based classification and its extensions. Effectively, our method combines the sparsity-based approaches with additional least-squares steps and exhitbits robustness to outliers achieving significant performance improvement with little additional cost. This approach also mitigates the need for a large number of training images since it proves robust to varying number of training samples.

@InProceedings{6952144,
  author = {M. Iliadis and L. Spinoulas and A. S. Berahas and H. Wang and A. K. Katsaggelos},
  booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
  title = {Sparse representation and least squares-based classification in face recognition},
  year = {2014},
  pages = {526-530},
  abstract = {In this paper we present a novel approach to face recognition. We propose an adaptation and extension to the state-of-the-art methods in face recognition, such as sparse representation-based classification and its extensions. Effectively, our method combines the sparsity-based approaches with additional least-squares steps and exhitbits robustness to outliers achieving significant performance improvement with little additional cost. This approach also mitigates the need for a large number of training images since it proves robust to varying number of training samples.},
  keywords = {face recognition;image classification;image representation;least squares approximations;least squares-based classification;sparse representation;face recognition;Training;Face recognition;Databases;Face;Dictionaries;Vectors;Robustness;Face recognition;sparse representation;classification},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569927015.pdf},
}

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