Face Recognition using Eigen-Faces

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This toolchain implements a simple face recognition toolchain based on Eigenfaces algorithm [EIGEN].

The toolchain is detailed as follows:

  • The images from the database are aligned according to the specified eye locations.
  • The PCA projection matrix is trained with a training set. This training set is composed by floating point vectors (64 bits) as a two-dimensional array; the number of rows corresponding to the number of training samples and the number of columns to the dimensionality of the training samples. The algorithm PCA can be used for this purpose.
  • The template for each client is computed as the average of the PCA projected features.
  • The distance between the probe PCA projected features and the client template is computed as scoring.
  • The analysis step integrates scores from the development and the test set.
[EIGEN]http://en.wikipedia.org/wiki/Eigenface
Updated Name Databases/Protocols Analyzers
tutorial/tutorial/full_eigenface/1/mobioMale_eigenfaces_50comp mobio/1@male tutorial/eerhter_postperf_iso/1
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