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Commit cd31364a authored by Olegs NIKISINS's avatar Olegs NIKISINS
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Added baseline doc for LBP+SVM on Replay-Mobile DB

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1 merge request!7Completed experiments for the Replay-Mobile and MSU MFSD DBs + HLDI's + updated preprocessors
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...@@ -141,9 +141,9 @@ The ROC curves for the particular experiment can be downloaded from here: ...@@ -141,9 +141,9 @@ The ROC curves for the particular experiment can be downloaded from here:
:download:`ROC curve <img/ROC_lbp_svm_replay_attack.pdf>` :download:`ROC curve <img/ROC_lbp_svm_replay_attack.pdf>`
------------ ------------
Image Quality Measures as features of facial region + SVM classifier Image Quality Measures as features of facial region + SVM classifier
======================================================================== ========================================================================
...@@ -249,6 +249,55 @@ The description of the database instance, which can be used to run face PAD expe ...@@ -249,6 +249,55 @@ The description of the database instance, which can be used to run face PAD expe
here :ref:`bob.pad.face.resources.databases.replay_mobile`. here :ref:`bob.pad.face.resources.databases.replay_mobile`.
LBP features of facial region + SVM classifier
========================================================================
Detailed description of this PAD pipe-line is given at :ref:`bob.pad.face.resources.face_pad.lbp_svm_replayattack`.
Note, that the same PAD pipe-line was used to run experiments on the Replay-Attack database.
To run this baseline on the `Replay-Mobile`_ database, using the ``grandtest`` protocol, execute the following:
.. code-block:: sh
$ ./bin/spoof.py lbp-svm \
--database replay-mobile --protocol grandtest --groups train dev eval \
--sub-directory <PATH_TO_STORE_THE_RESULTS>
.. tip::
Similarly to the tip above you can run this baseline in parallel.
To understand the settings of this baseline PAD experiment you can check the
corresponding configuration file: ``bob/pad/face/config/lbp_svm.py``
To evaluate the results computing EER, HTER and plotting ROC you can use the
following command:
.. code-block:: sh
./bin/evaluate.py \
--dev-files <PATH_TO_STORE_THE_RESULTS>/grandtest/scores/scores-dev \
--eval-files <PATH_TO_STORE_THE_RESULTS>/grandtest/scores/scores-eval \
--legends "LBP features of facial region + SVM classifier + Replay-Mobile database" \
-F 7 \
--criterion EER \
--roc <PATH_TO_STORE_THE_RESULTS>/ROC.pdf
The EER/HTER errors for the `Replay-Mobile`_ database are summarized in the Table below:
+-------------------+----------+----------+
| Protocol | EER,\% | HTER,\% |
+===================+==========+==========+
| ``grandtest`` | 13.814 | 17.174 |
+-------------------+----------+----------+
The ROC curves for the particular experiment can be downloaded from here:
:download:`ROC curve <img/ROC_lbp_svm_replay_mobile.pdf>`
------------
Image Quality Measures as features of facial region + SVM classifier Image Quality Measures as features of facial region + SVM classifier
======================================================================== ========================================================================
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