computational-geometry

Currently, I am working on a project that is trying to group 3d points from a dataset by specifying connectivity as a minimum euclidean distance. My algorithm right now is simply a 3d adaptation of the naive flood fill. size_t PointSegmenter::growRegion(size_t & seed, size_t segNumber) { size_t numPointsLabeled = 0; //alias for points to avoid retyping vector<Point3d> & points = _img.points; deque<size_t> ptQueue; ptQueue.push_back(seed); points[seed].setLabel(segNumber); while (!ptQueue.empty()) { size_t currentIdx = ptQueue.front(); ptQueue.pop_front(); points[currentIdx].setLabel(segNumber)

I am currently working on a project which deals with geometric problems. Since this project will be used commercially I cannot use libraries like CGAL. I am currently using boost::geometry with inexact types but I encountered numeric issues. I tried to simply use an exact point type from boost::multiprecision but it doesn't compile when I call boost::geometry functions. I found this page which shows how to use a numeric_adaptor to use boost::geometry with exact number types. However, it seems outdated and I wasn't able to make it work. Can boost::geometry be used with exact number types ? How

This is a problem I came across frequently and I'm searching a more effective way to solve it. Take a look at this pics: Let's say you want to find the shortest distance from the red point to a line segment a n . Assume you only know the start/end point (x,y) of the segments and the point. Now this can be done in O(n), where n are the line segments, by checking every distance from the point to a line segment. This is IMO not effective, because in the worst case there have to be n-1 distance checks till the right one is found. This can be a real performance issue for n = 1000 f.e. (which is a

I have a lot of polygons, and after I do a union of all these polygons, I get a new, big polygon. The union algorithm is a black box and using third-party-library process, which I couldn't control, and neither can I hope to extract any information out kind of progress. Is there efficient way for me to know, for every edge of that big gigantic unionized polygon, which of it is belonging to which edge of the smaller polygon? A brute force way to solve this problem is to compare every edge of the unionized polygon with each of the smaller polygons, but this is going to be very inefficient. Any

There is a class of algorithms for triangulation between two planar contours. These algorithms try to make a "good triangulation" to fill a space between these contours: One of them ( Optimal surface reconstruction from planar contours ) is based on the dynamic programming technique and uses a cost function for determining which triangulation is acceptable according to the minimum cost. A minimal triangle area as a cost function makes a good result in most of cases ( Triangulation of Branching Contours using Area Minimization ), but, unfortunately, not in all of them. For example when you have