Enrolls a graph template from several enrollment graphs

This algorithm is a legacy one. The API has changed since its implementation. New versions and forks will need to be updated.
This algorithm is splittable

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.

Unnamed group

Endpoint Name Data Format Nature
graph siebenkopf/graph/1 Input
model_id system/uint64/1 Input
graph_model siebenkopf/graph_model/3 Output

The code for this algorithm in Python
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This algorithm enrolls a template from several enrollment graphs. Here, we follow the idea of the bunch graph [Wiskott97] by simply storing all models.

[Wiskott97]Laurenz Wiskott, Jean-Marc Fellous, Norbert Krueger, Christoph Von Der Malsburg. Face Recognition By Elastic Bunch Graph Matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997.

Experiments

Updated Name Databases/Protocols Analyzers
siebenkopf/siebenkopf/FaceRec-WithOut-Training/2/XM2VTS-PhaseDiff xm2vts/1@darkened-lp1 siebenkopf/ROC/15,siebenkopf/EER_HTER/8
siebenkopf/siebenkopf/FaceRec-WithOut-Training/2/XM2VTS-ScalarProduct xm2vts/1@darkened-lp1 siebenkopf/ROC/15,siebenkopf/EER_HTER/8
siebenkopf/siebenkopf/FaceRec-WithOut-Training/2/XM2VTS-Canberra xm2vts/1@darkened-lp1 siebenkopf/ROC/15,siebenkopf/EER_HTER/8
siebenkopf/siebenkopf/FaceRec-WithOut-Training/2/Banca_P-ScalarProduct banca/1@P siebenkopf/ROC/15,siebenkopf/EER_HTER/8
siebenkopf/siebenkopf/FaceRec-WithOut-Training/2/Banca_P-Canberra banca/1@P siebenkopf/ROC/14,siebenkopf/EER_HTER/8
siebenkopf/siebenkopf/FaceRec-WithOut-Training/2/Banca_P-PhaseDiff banca/1@P siebenkopf/ROC/14,siebenkopf/EER_HTER/8

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.

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