Rotationally Invariant Descriptors using Intensity Order ... - IEEE Xplore

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IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 16
(a) (b) (c) (d) (e)
Fig. 6. The selection of 4 support regions and their normalization. Each color corresponds to a boundary of one support region
and all the support regions are normalized to a circular region with unified radius. (a) shows the selected support regions and
(b)-(e) are the normalized regions.
Fig. 7. The procedure of pooling local features based on their intensity orders for a support region. See text for details.
paper, we set ri =1+0.5 × (i − 1) such that the support regions have an equal increment
of radius as plotted in Fig. 6(a). In each support region, the rotation invariant local features of
all the sample points are then pooled by their intensity orders. As shown in Fig. 7, first they
are pooled together to form a vector in each partition which is obtained based on the intensity
orders of sample points and then the accumulated vectors of different partitions are concatenated
together to represent this support region. We denote it as D(R) =(F (R1),F(R2), ··· ,F(Rk))
and F (Ri) is the accumulated vector of partition Ri, i.e.,
F (Ri) =
FG(X) (14)
X∈Ri
November 26, 2011 DRAFT