KDTree.cpp

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#include "lvr2/registration/KDTree.hpp"
#include "lvr2/registration/AABB.hpp"
 
namespace lvr2
{
 
class KDNode : public KDTree
{
public:
    KDNode(int axis, double split, KDTreePtr& lesser, KDTreePtr& greater)
        : axis(axis), split(split), lesser(move(lesser)), greater(move(greater))
    { }
 
protected:
    virtual void nnInternal(const Point& point, Neighbor& neighbor, double& maxDist) const override
    {
        double val = point(this->axis);
        if (val < this->split)
        {
            this->lesser->nnInternal(point, neighbor, maxDist);
            if (val + maxDist >= this->split)
            {
                this->greater->nnInternal(point, neighbor, maxDist);
            }
        }
        else
        {
            this->greater->nnInternal(point, neighbor, maxDist);
            if (val - maxDist <= this->split)
            {
                this->lesser->nnInternal(point, neighbor, maxDist);
            }
        }
    }
 
private:
    int axis;
    double split;
    KDTreePtr lesser;
    KDTreePtr greater;
};
 
class KDLeaf : public KDTree
{
public:
    KDLeaf(Point* points, int count)
        : points(points), count(count)
    { }
 
protected:
    virtual void nnInternal(const Point& point, Neighbor& neighbor, double& maxDist) const override
    {
        double maxDistSq = maxDist * maxDist;
        bool changed = false;
        for (int i = 0; i < this->count; i++)
        {
            double dist = (point - this->points[i]).squaredNorm();
            if (dist < maxDistSq)
            {
                neighbor = &this->points[i];
                maxDistSq = dist;
                changed = true;
            }
        }
        if (changed)
        {
            maxDist = sqrt(maxDistSq);
        }
    }
 
private:
    Point* points;
    int count;
};
 
KDTreePtr create_recursive(KDTree::Point* points, int n, int maxLeafSize)
{
    if (n <= maxLeafSize)
    {
        return KDTreePtr(new KDLeaf(points, n));
    }
 
    AABB<float> boundingBox(points, n);
 
    int splitAxis = boundingBox.longestAxis();
    double splitValue = boundingBox.avg()(splitAxis);
 
    if (boundingBox.difference(splitAxis) == 0.0) // all points are exactly the same
    {
        // this case is rare, but would lead to an infinite recursion loop if not handled,
        // since all Points would end up in the "lesser" branch every time
 
        // there is no need to check all of them later on, so just pretend like there is only one
        return KDTreePtr(new KDLeaf(points, 1));
    }
 
    int l = splitPoints(points, n, splitAxis, splitValue);
 
    KDTreePtr lesser, greater;
 
    if (n > 8 * maxLeafSize) // stop the omp task subdivision early to avoid spamming tasks
    {
        #pragma omp task shared(lesser)
        lesser  = create_recursive(points    , l    , maxLeafSize);
 
        #pragma omp task shared(greater)
        greater = create_recursive(points + l, n - l, maxLeafSize);
 
        #pragma omp taskwait
    }
    else
    {
        lesser  = create_recursive(points    , l    , maxLeafSize);
        greater = create_recursive(points + l, n - l, maxLeafSize);
    }
 
    return KDTreePtr(new KDNode(splitAxis, splitValue, lesser, greater));
}
 
KDTreePtr KDTree::create(SLAMScanPtr scan, int maxLeafSize)
{
    KDTreePtr ret;
 
    size_t n = scan->numPoints();
    auto points = boost::shared_array<Point>(new Point[n]);
 
    #pragma omp parallel for schedule(static)
    for (size_t i = 0; i < n; i++)
    {
        points[i] = scan->point(i).cast<PointT>();
    }
 
    #pragma omp parallel // allows "pragma omp task"
    #pragma omp single // only execute every task once
    ret = create_recursive(points.get(), n, maxLeafSize);
 
    ret->points = points;
 
    return ret;
}
 
 
size_t KDTree::nearestNeighbors(KDTreePtr tree, SLAMScanPtr scan, KDTree::Neighbor* neighbors, double maxDistance, Vector3d& centroid_m, Vector3d& centroid_d)
{
    size_t found = KDTree::nearestNeighbors(tree, scan, neighbors, maxDistance);
 
    centroid_m = Vector3d::Zero();
    centroid_d = Vector3d::Zero();
 
    for (size_t i = 0; i < scan->numPoints(); i++)
    {
        if (neighbors[i] != nullptr)
        {
            centroid_m += neighbors[i]->cast<double>();
            centroid_d += scan->point(i);
        }
    }
 
    centroid_m /= found;
    centroid_d /= found;
 
    return found;
}
 
size_t KDTree::nearestNeighbors(KDTreePtr tree, SLAMScanPtr scan, KDTree::Neighbor* neighbors, double maxDistance)
{
    size_t found = 0;
    double distance = 0.0;
 
    #pragma omp parallel for firstprivate(distance) reduction(+:found) schedule(dynamic,8)
    for (size_t i = 0; i < scan->numPoints(); i++)
    {
        if (tree->nearestNeighbor(scan->point(i), neighbors[i], distance, maxDistance))
        {
            found++;
        }
    }
 
    return found;
}
 
}