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transitions) is not. In the computation of the LBP histogram, the

histogram has a separate bin for every uniform pattern, and all

non-uniform patterns are assigned to a single bin. Using uniform

patterns, the length of the feature vector for a single cell reduces

from 256 to 59. The 58 uniform binary patterns correspond to the

integers 0, 1, 2, 3, 4, 6, 7, 8, 12, 14, 15, 16, 24, 28, 30, 31, 32, 48,

56, 60, 62, 63, 64, 96, 112, 120, 124, 126, 127, 128, 129, 131, 135,

143, 159, 191, 192, 193, 195, 199, 207, 223, 224, 225, 227, 231, 239,

240, 241, 243, 247, 248, 249, 251, 252, 253, 254 and 255.

• Over-Complete Local Binary Patterns (OCLBP):cite-ref-9[9] OCLBP is a variant of

LBP that has been shown to improve the overall performance on face

verification. Unlike LBP, OCLBP adopts overlapping to adjacent blocks.

Formally, the configuration of OCLBP is denoted as S : (a, b, v, h, p,

r): an image is divided into a×b blocks with vertical overlap of v and

horizontal overlap of h, and then uniform patterns LBP(u2,p,r) are

extracted from all the blocks. Moreover, OCLBP is composed of several

different configurations. For example, in their original paper, the

authors used three configurations: S :

(10,10,12,12,8,1),(14,14,12,12,8,2),(18,18,12,12,8,3). The three

configurations consider three block sizes: 10×10, 14×14, 18×18, and half

overlap rates along the vertical and horizontal directions. These

configurations are concatenated to form a 40877 dimensional feature

vector for an image of size 150x80.

• Transition Local Binary Patterns(tLBP):cite-ref-10[10] binary value of transition

coded LBP is composed of neighbor pixel comparisons clockwise direction

for all pixels except the central.

• Direction coded Local Binary Patterns(dLBP): the dLBP encodes the

intensity variation along the four basic directions through the central

pixel in two bits.

• Multi-block LBP: the image is divided into many blocks, a LBP

histogram is calculated for every block and concatenated as the final

histogram.

• Volume Local Binary Pattern(VLBP):cite-ref-11[11] VLBP looks at dynamic texture

as a set of volumes in the (X,Y,T) space where X and Y denote the

spatial coordinates and T denotes the frame index. The neighborhood of a

pixel is thus defined in three dimensional space, and volume textons can

be extracted into histograms.

• RGB-LBP: This operator is obtained by computing LBP over all three

channels of the RGB color space independently, and then concatenating

the results together.

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