| Input: The structure in external storage of FMRH. |
| Output: The set of cluster . |
| Description: This algorithm generates the set of cluster |
| by traversing the structure of FMRH with depth-first order, |
| according to the relationship of static error and threshold. |
| (1) Initialization: |
| (1.1) According to Definition 1, set |
| , |
| and make |
|
|
| . |
| (1.2) Clear the clusters in aggregation . |
| (2) Recall the function of Traverse_FMRH (FMRH, , 0). |
| (3) Generate the index file of clusters, and save the index of data block for each cluster. |
| (4) The end. |
| Traverse_FMRH (FMRH, current_Block, level_S) |
| Function Description: Load static error of data blocks in |
| FMRH, and decide which cluster it belongs to. |
| Parameter Description: FMRH is a multi-resolution |
| level of structure based on features. The parameter |
| current_Block is the current data block. The parameter |
| level_S is the index of current data block in the level. |
| (1) Load the static error of current_Block from FMRH as current_Block.CovSE. |
| (2) Decide which cluster current_Block belongs to: |
| (2.1) Construct intervals according to error |
| thresholds . |
| (2.2) Each threshold interval corresponds a cluster from to : |
| (2.2.1) Decide the size of current_Block.CovSE, if it meet two constraints: |
| ① ; |
| ② add data block current_Block into the cluster , |
| if there is no ancestor data block of current_Block |
| including in the cluster . |
| (2.2.2) When current_Block.leaf is false, then, get four data |
| blocks in the next level |
| from current_Block in FMRH, and recall the function of |
| DeepTraverse_FMRH(FMRH, , level_S + 1). |
| (3) The end. |
