Linus Schaub, 2022
Simple kd-tree data structure to store and find 3D points.
We use the three classes KDTree, Axis-Aligned-Bounding-Box (AABB) and Point
To insert a point, the insert method can be used: insert. It takes a pointer to a point and will add the point to the kdtree.
To determine if a given point is already in the kdtree, the find_point method can be used. It will return a pointer to the found point or a nullptr if no point at the same position was found.
The nearest neighbor to a given point can be found with the find_nearest method. If no point was found (the kdtree is empty), nullptr will be returned. To determine the distance of a given point p and the found nearest point f can be determined with this line:
Point *p = new Point(2.5, 1, 10);
Point *f = kdtree.find_nearest(p);
float distance = (*p - *f).length();
cd buildcmake ..make./kdtree-cpp
The search performance was evaluated at different tree sizes. At each tree size, 100 points were searched and the duration was averaged. The plot below shows the average search duration by kd-tree point count.
