Bob 2.0 implementation of ISV client model training. Input template ids are strings.
Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.
Endpoint Name  Data Format  Nature 

statistics  tutorial/gmm_statistics/1  Input 
template_id  system/text/1  Input 
model  tpereira/isvmachine/1  Output 
Endpoint Name  Data Format  Nature 

ubm  tutorial/gmm/1  Input 
isvbase  tpereira/isvbase/1  Input 
Parameters allow users to change the configuration of an algorithm when scheduling an experiment
Name  Description  Type  Default  Range/Choices 

isvenrolliterations  uint32  1 
The code for this algorithm in Python
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Given a feature vector, a GMM and a U subspace, computes the Intersession Variability Modeling (ISV) client model. Basically, this algorithm computes the latent variable z_{i} excluding possible session factors (described by the latent variable x_{i, j}).
Specific details can be found in [McCool2013]:
This algorithm relies on the Bob library.
The inputs are:
The output, model, is the latent variable z_{i} (Eq. (31) in McCool2013) that corresponds to the client offset (with the session variations suppressed).
[McCool2013] 

Updated  Name  Databases/Protocols  Analyzers  

pkorshunov/pkorshunov/isvasvpadfusioncomplete/1/asv_isvpad_lbp_hist_ratios_lrfusion_lrpa_aligned  avspoof/2@physicalaccess_verify_train_spoof,avspoof/2@physicalaccess_antispoofing,avspoof/2@physicalaccess_verification,avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verify_train  pkorshunov/spoofscorefusionroc_hist/1  
pkorshunov/pkorshunov/isvasvpadfusioncomplete/1/asv_isvpad_gmmfusion_lrpa  avspoof/2@physicalaccess_verify_train_spoof,avspoof/2@physicalaccess_antispoofing,avspoof/2@physicalaccess_verification,avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verify_train  pkorshunov/spoofscorefusionroc_hist/1  
pkorshunov/pkorshunov/isvspeakerverificationspoof/1/isvspeakerverificationspoofpa  avspoof/2@physicalaccess_verification,avspoof/2@physicalaccess_verification_spoof  pkorshunov/eerhter_postperf_iso_spoof/1  
pkorshunov/pkorshunov/isvspeakerverification/1/isvspeakerverificationlicit  avspoof/2@physicalaccess_verification  pkorshunov/eerhter_postperf_iso/1 
This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.