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.
- hist
Segment histograms.
Options:
- bk.hists_per_im
The number of histograms to select from each training image. If hists_per_cat is set, this has no effect. Default 50
- bk.hists_per_cat
The number of histograms to select per category. Default [] uses hist_per_im.
- bk.seg_neighbors
The size of the superpixel neighborhood. Default 0.
- bk.rand_seed
Set the random seed before proceeding. Default [] does not change the random seeds.
Fetchable attributes:
- train_ids
Returns [train_ids labels]. train_ids is a Nx2 vector, where the first column denotes the seg_id and the second column denotes the superpixel.