In this tutorial we will introduce the biometric recognition framework of Bob. This framework includes both the implementation of evaluation protocols for several publicly available datasets, as well as implementations of many biometric recognition algorithms, while it is still easy to extend. This framework makes it easy to provide reproducible research, and several reproducible research papers have been published using Bob and its biometric recognition framework.
On the basis of face recognition examples, participants will be made familiar with the structure of a biometric recognition experiment including concepts of feature extraction, model enrollment, score computation, and evaluation. In three hands-on exercises, the participants will run three very different face recognition algorithms. After starting with a simple Eigenface approach, the more complex algorithm of Gaussian mixture modeling of DCT features will be introduced and evaluated. Finally, we will extend the framework by introducing a new algorithm, i.e., extracting deep features from the publicly available VGG face network using the Python interface of Caffe.
[YOUR_ATNT_DIRECTORY] = /path/to/your/directory/att_facesIt is a bit confusing as the reader cannot easily distinguish if it should not replace "[YOUR_ATNT_DIRECTORY]" string as well. As a matter of fact, we should change this in bob.bio.base to something a bit more obvious. Maybe suppressing the word "YOUR" will do the trick.
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Hey Manuel,Very nice and complete :-)This definitely should be in the Bob's webpage.Cheers
On Thu, Oct 12, 2017 at 2:44 AM, 'Manuel Günther' via bob-devel <bob-...@googlegroups.com> wrote:
The videos for the tutorial are now uploaded on my Youtube channel: https://www.youtube.com/channel/UCasPC00f6pQ3ZCyAcbxOUJg/videosWe should think about how to link them to the Bob webpage.Enjoy!
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----Tiago
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