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authornunzip <np.scarh@gmail.com>2018-11-16 17:32:58 +0000
committernunzip <np.scarh@gmail.com>2018-11-16 17:32:58 +0000
commit702cbeec081f884d336c5b61b8717b9df5b4c48b (patch)
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parent55e4c2c148c1e4b0714671da774954d739548fb6 (diff)
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@@ -5,17 +5,20 @@ author:
affilation: Imperial College
location: London, UK
email: vz215@ic.ac.uk, np@ic.ac.uk
-keywords:
- - one
- - two
- - three
numbersections: yes
lang: en
babel-lang: english
abstract: |
- This is the abstract for the pattern recognition courswork.
+ In this coursework we will analyze the benefits of different face recognition methods.
+ On one hand we will analyze PCA, Principal Components Analysis. This method
+ allows dimensionality reduction, obtaining a generative subspace which is very reliable for
+ face reconstruction.
- It consists of two paragraphs.
+ On the other hand LDA, Linear Discriminant Analysis, allows to perform a very reliable classification,
+ generating a discriminative subspace, in which the separation between classes is easier to recognize.
+
+ In the final part we will analyze the benefits of using a combined version of the two methods using FIsherfaces.
+ As we will see, the PCA-LDA ensemble will obtain much more accurate results with a very high speed of computation.
...