Documentaton - BLOCKS - BLOCK_TEST_SEGCRF

Superpixel CRF, as proposed in Fulkerson et. al 2009.

BK = BLOCK_TEST_SEGCRF() Initializes the block with the default options.

BK = BLOCK_TEST_SEGCRF(BK) Executes the block with options and inputs BK.

Required inputs:

db

The database.

qseg

The quick shift segmentations.

segloc

The unary potentials, in the form output by BLOCK_TEST_SEGLOC()

traincrf

Parameters for the crf, from BLOCK_TRAIN_CRF()

Options:

bk.rand_seed

Set the random seeds before proceeding. Default of [] does not change the seeds.

bk.restrict

Restrict the possible solutions of the CRF to include only those which have co-occurred in the training data. Default 0.

Fetchable attributes:

test

Classification result (images). Returns [class confidence] for required input: seg_id.

segtest

Classification result (superpixels). Returns [class confidence] for required input: seg_id. class is a vector Nx1 where N is the number of superpixels. confidence is a matrix Nx1 cell array, where each cell is a Cx1 vector expressing the confidence in each of C classes.