Morpho (version 2.1)

icpmat: match two landmark configurations using iteratively closest point search

Description

match two landmark configurations using iteratively closest point search

Usage

icpmat(x, y, iterations, mindist = 1e+15, subsample = NULL, scale = FALSE)

Arguments

x

moving landmarks

y

target landmarks

iterations

integer: number of iterations

mindist

restrict valid points to be within this distance

subsample

use a subsample determined by kmean clusters to speed up computation

scale

logical: if TRUE, scaling is allowed

Value

• returns the rotated landmarks

Examples

data(nose)
icp <- icpmat(shortnose.lm,longnose.lm,iterations=10,subsample = 20)

##2D example  using icpmat to determine point correspondences
require(shapes)
## we scramble rows to show that this is independent of point order
moving <- gorf.dat[sample(1:8),,1]
plot(moving,asp=1) ## starting config
icpgorf <- icpmat(moving,gorf.dat[,,2],iterations = 20)
points(icpgorf,asp = 1,col=2)
points(gorf.dat[,,2],col=3)## target

## get correspondences using nearest neighbour search
index <- mcNNindex(icpgorf,gorf.dat[,,2],k=1,cores=1)
icpsort <- icpgorf[index,]
for (i in 1:8)
lines(rbind(icpsort[i,],gorf.dat[i,,2]))