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Laboratoire d'InfoRmatique en Image et Systèmes d'information

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Laboratoire d'InfoRmatique en Image et Systèmes d'information
UMR 5205 CNRS / INSA Lyon / Université Claude Bernard Lyon 1 / Université Lumière Lyon 2 / École Centrale de Lyon
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International conference with reviewing committee

Triangular Similarity Metric Learning for Face Verification [PDF]
Lilei Zheng [LIRIS] , Khalid Idrissi [LIRIS] , Christophe Garcia [LIRIS] , Stefan Duffner [LIRIS] , Atilla Baskurt [LIRIS]
5/2015
Dans 11th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2015) , Ljubljana. pp. 1-7.

HAL : hal-01158908

Abstract

We propose an efficient linear similarity metric learning method for face verification called Triangular Similarity Metric Learning (TSML). Compared with the relevant stateof-the-art work, this method improves the efficiency of learning the cosine similarity while keeping effectiveness. Concretely, we present a geometrical interpretation based on the triangle inequality for developing a cost function and its efficient gradient function. We formulate the cost function as an optimization problem and solve it with the advanced L-BFGS optimization algorithm. We perform extensive experiments on the LFW data set using four descriptors: LBP, OCLBP, SIFT and Gabor wavelets. Moreover, for the optimization problem, we test two kinds of initialization: the identity matrix and the WCCN matrix. Experimental results demonstrate that both of the two initializations are efficient and that our method achieves the state-of-the-art performance on the problem of face verification.

BibTex

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@InProceedings{Liris-7042,
  title         = {{Triangular Similarity Metric Learning for Face 
    Verification}},
  author        = {Lilei {Zheng} and Khalid {Idrissi} and Christophe {Garcia} 
    and Stefan {Duffner} and Atilla {Baskurt}},
  year          = {2015},
  month         = may,
  booktitle     = {11th IEEE International Conference on Automatic Face and 
    Gesture Recognition (FG 2015) },
  pages         = {1-7}, 
  language      = {en},
  url           = {http://liris.cnrs.fr/publis/?id=7042}
}