| Require: |
| PrunedList: a list of obstacle information (OI) resulting fom the pruning step. |
| : Local density radius. |
| percentageOfObstInfToBeFiltered: percentage of OI to be filtered out. |
| Ensure: FilteredList: a list containing the kept points (positions). |
| ▹ convert the list of position pairs (OI) to a list of positions (points) |
| () LP: List ▹ list of points |
| () for each obstacleInformation in PrunedList do |
| () .Add(.LeftExtremity) |
| () .Add(.RightExtremity) |
| () end for |
| ▹ For each point we calculate its local density (i.e. the number of points (neighbours) whose distance |
| with the current point is less than |
| () nbOfNeighbours[.size] ▹ array in which we save the local density of each point |
| () for (; .size; ) do |
| () nbOfNeighbours[] ← 0 |
| () end for |
| () maxDensity ← 0 |
| () for (; .size; ) do |
| () for (; .size; ) do |
| () if (euclidianDistance([], []) < ) then |
| () nbOfNeighbours[]++ |
| () end if |
| () end for |
| (17) if (nbOfNeighbours[] > maxDensity) then |
| () maxDensity ← nbOfNeighbours[] |
| () end if |
| () end for |
| () locDensHist[maxDensity + 1] ▹ an array in which we will calculate the local density histogram |
| () for (; ≤ locDensHist.size; ) do |
| () locDensHist[] ← 0 |
| () end for |
| () for (; ≤ .size; ) do |
| () locDensHist[nbOfNeighbours[]]++ |
| () end for |
| () nbOfObstacleInformationToBeFiltered ← .size/100 percentageOfObstInfToBeFiltered |
| () sumOfObstInf ← 0 |
| () localDensityThreshold ← positiveInfinity |
| () for (; ≤ locDensHist.size; ) do |
| () sumOfObstInf += localDensityHistogram[] |
| () if (sumOfObstInf > nbOfObstacleInformationToBeFiltered) then |
| () localDensityThreshold ← |
| () break ▹ leave the loop |
| () end if |
| () end for |
| () FilteredList: List |
| () for (; ≤ .size; ) do |
| () if (nbOfNeighbours[] ≥ localDensityThreshold) then |
| () FilteredList.Add([]) |
| () end if |
| () end for |
| () return FilteredList |
