Perform a photometric normalization on the given (aligned) image
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 |
|---|---|---|
| image | system/array_2d_uint8/1 | Input |
| preprocessed | system/array_2d_floats/1 | Output |
The code for this algorithm in Python
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The photometric normalization is accoring to [Tan07], which is implemented in bob.ip.base.TanTriggs. Although the original algorithm has some parameters, we here stick to the ones from [Tan07].
| [Tan07] | (1, 2) Xiaoyang Tan and Bill Triggs. Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions. International Conference on Analysis and Modeling of Faces and Gestures, 2007 |
| 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.