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align two 3D-pointclouds/meshes by their principal axes
pcAlign(x, y, optim = TRUE, subsample = NULL, iterations = 10,
mc.cores = 2)# S3 method for matrix
pcAlign(x, y, optim = TRUE, subsample = NULL,
iterations = 10, mc.cores = 2)
# S3 method for mesh3d
pcAlign(x, y, optim = TRUE, subsample = NULL,
iterations = 10, mc.cores = 2)
matrix or mesh3d
matrix or mesh3d, if missing, x will be centered by its centroid and aligned by its princial axis.
logical if TRUE, the RMSE between reference and target will be minimized testing all possible axes alignments and (if iterations > 0) followed by a rigid ICP procedure.
integer: use subsampled points to decrease computation time of optimization.
integer: number of iterations for optimization (the higher the more accurate but also more time consuming).
use parallel processing to find best alignment to original shape.
rotated and translated version of x to the center and principal axes of y.
x and y will first be centered and aligned by their PC-axes. If optim=TRUE,all possible 8 ordinations of PC-axes will be tested and the one with the smallest RMSE between the transformed version of x and the closest points on y will be used. Then the rotated version of x is translated to the original center of mass of y.
# NOT RUN {
data(boneData)
blm1 <- pcAlign(boneLM[,,1],boneLM[,,2])
# }
# NOT RUN {
require(rgl)
spheres3d(boneLM[,,1])#original position
spheres3d(blm1,col=2)#aligned configuration
spheres3d(boneLM[,,2],col=3)#target
# }
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