Algorithm 2 Hierarchical STPS method |
1: |
i:=1; assume that an parameter net is given |
2: |
repeat |
3: |
Create icosahedral samples at level i for α’s and β’s |
4: |
if i=1 then
|
5: |
Rotate the parameter net using each (αβ0), apply STPS, and keep the top K candidates that minimize the distortion costs, defined in Section 4.2.3 |
6: |
else
|
7: |
Keep only local icosahedral samples for α’s & β’s |
8: |
Rotate the parameter net of each top K candidate using each (αβ0), apply STPS, and select top K candidates |
9: |
i:=i+1 |
10: |
until The best distortion costs do not improve |
11: |
Return the best result in top K list |