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.

Group: main

Endpoint Name Data Format Nature
image system/array_2d_uint8/1 Input
features system/array_2d_floats/1 Output

Parameters allow users to change the configuration of an algorithm when scheduling an experiment

Name Description Type Default Range/Choices
regions_cols Number of regions in column uint8 8 [1, 100]
lbp_maxradius Maxmum radius of milti LBP uint8 1 [1, 10]
regions_rows Number of regions in row uint8 8 [1, 100]
lbp_minradius Minimum radius of milti LBP uint8 1 [1, 10]
lbp_circular LBP Circular bool True
lbp_uniform LBP Uniform bool True
lbp_neighbor_count LBP Neighbour count uint8 8 [8, 32]

The code for this algorithm in Python
The ruler at 80 columns indicate suggested POSIX line breaks (for readability).
The editor will automatically enlarge to accomodate the entirety of your input
Use keyboard shortcuts for search/replace and faster editing. For example, use Ctrl-F (PC) or Cmd-F (Mac) to search through this box

Refer to: Chi-Ho Chan, Josef Kittler, Kieron Messer: Multi-scale Local Binary Pattern Histograms for Face Recognition. 809-818

Experiments

Updated Name Databases/Protocols Analyzers
smarcel/chichan/full_pre_mlbphs_projection/2/mobio-f_TT_MLBPH_PCA98_LDA300_postperf-iso mobio/2@female tutorial/eerhter_postperf_iso/1
smarcel/chichan/full_pre_mlbphs_projection/2/mobio-m_TT_MLBPH_PCA98_LDA300_postperf-iso mobio/2@male tutorial/eerhter_postperf_iso/1
smarcel/chichan/full_pre_mlbphs_projection/2/mobio-m_TT_MLBPH_PCA98_postperf-iso mobio/2@male tutorial/eerhter_postperf_iso/1
smarcel/chichan/full_pre_mlbphs_projection/2/mobio-f_TT_MLBPH_PCA98_postperf-iso mobio/2@female tutorial/eerhter_postperf_iso/1
chichan/chichan/full_pre_mlbphs_projection/2/Prep_MLBPH_XM2VTS_nouniform_PCA xm2vts/1@lp1,xm2vts/1@darkened-lp1 tutorial/eerhter_postperf/1
chichan/chichan/full_pre_mlbphs_projection/2/Prep_MLBPH_XM2VTS_LDA xm2vts/1@lp1,xm2vts/1@darkened-lp1 tutorial/eerhter_postperf/1
chichan/chichan/full_pre_mlbphs_projection/2/Prep_MLBPH_XM2VTS_no_uniform_p98LDA xm2vts/1@lp1,xm2vts/1@darkened-lp1 tutorial/eerhter_postperf/1
chichan/chichan/full_pre_mlbphs_projection/2/Prep_MLBPH_XM2VTS_PCA xm2vts/1@lp1,xm2vts/1@darkened-lp1 tutorial/eerhter_postperf/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.

Terms of Service | Contact Information | BEAT platform version 1.5.0b0 | © Idiap Research Institute - 2013-2019