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. 2016 Feb 24;16(3):280. doi: 10.3390/s16030280
Algorithm 1. Spatial Consensus Check
Input: {(ΔxknG,ΔyknG), ,(ΔxkG,ΔykG),(ΔxknD,ΔyknD), ,(ΔxkD,ΔykD)}
Output: {(Δx¯k, Δy¯k)}
for i = 1 to n do
Δx˜kiG = xi1GΔxk1G++xiiGΔxkiG+θxi1GΔyk1G++θxiiGΔykiG
Δx˜kiD = xi1DΔxk1D++xiiDΔxkiD+θxi1DΔyk1D++θxiiDΔykiD
Δy˜kiG = yi1GΔxk1G++yiiGΔxkiG+θyi1GΔyk1G++θyiiGΔykiG
Δy˜kiD = yi1DΔxk1D++yiiDΔxkiD+θyi1DΔyk1D++θyiiDΔykiD
end
n1' = n2' =n
for i = 1 to Max_iters do
Δx¯k = Δx˜k1G++Δx˜kn1'G+Δx˜k1D++Δx˜kn2'D+ΔxkG+ΔxkDn1' + n2'+2
Δy¯k = Δy˜k1G++Δy˜kn1'G+Δy˜k1D++Δy˜kn2'D+ΔykG+ΔykDn1' + n2'+2
  Compute the distance L of all n1' + n2'+2 points to centroid points.
  For a point (Δx, Δy), denotes L = sum(L)  L(n1' + n2'+2)  1
  if (Δx, Δy)  (Δx¯, Δy¯)L¯>threshold, then
    Remove this point.
    Update n1'  or n2'.
  end
end