I'm trying to understand how quickhull works in 3D. I already understand how the algorithm works in 2D but I just don't get how the algorithm can be implemented in 3D space. Are there any tutorials or papers that can help me?
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I was suggested to create a GA algorithm to solve the problem of linear intersections identification in 2d space. I have been thinking to modify the sweep line algorithm or a similar one (like Bentley Ottman) and create a GA algorithm.
I have been studying the literature and i also came accross "Overlay of Subdivisions" problem which is quite similar, but for multiple layers of data. Not a lot information on that problem and i am struggling to understand the algorithm.
I am now thinking that in the first case a GA optimization is impossible but maybe it is possible for the overlay of subdivisions problem.
Anyone with more experience thinks that this will work or am i looking for the impossible?
I have the task to implement the creation of a visibility graph based on a set of simple polygons which are given by the task. The polygons have positive whole number coordinates and can be non-convex. I wanted to implement the rotational plane sweep algorithm which was mentioned in the lecture but not very well explained.
The only other source I could find about this algorithm was this page, that did not make it fully clear either: https://tanergungor.blogspot.com/2015/04/robot-navigation-rotational-sweep.html
I would appreciate it if someone could explain the rotational plane sweep algorithm to an extent which I can understand.
Here is a screenshot of an example obstacle arrangement with my attempt at a solution which is not yet working and more or less based on trial and error rather than understanding and implementing the actual algorithm. The algorithm is just using a single vertex which is not located on a polygon in this example.
I am trying to approach non-rigid alignment using Convex Mixed-Integer Algorithm, but I am new to computer vision. Does anyone know some sample code that is similar - so that I can use that as a reference?
The algorithm is based on this research paper:
MINA: Convex Mixed-Integer Programming for Non-Rigid Shape Alignment
Thank you for showing interest in our work.
We model the constrained optimization problem in MATLAB with the help of YALMIP library and solve it using MOSEK.
I am wondering whether there are any algorithms that use the Akl-Toussaint throw-away heuristic to compute the convex hull in 3D (not just as a simple pre-processing, but as the algorithmic principle or building block). And if so, what would their expected time complexity be?
Also, I am interested in experimental comparisons of such algorithms with the more traditional algorithms in 3D (e.g., Clarkson-Shor).
I would appreciate it very much if you could point me to papers or web pages that shed some light on my questions. (Or answer them directly :-) )
I have spent time looking for information on the best algorithm to create a nesting of irregular polygons in 2D using manual and automatic positioning. I need to use such an algorithm in the context of CAD/CAM software. Here are the real possibilities I've found so far:
Separating Axis Theorem: is a fairly quick and simple algorithm to implement, but the drawback I find with it is that it only works with convex polygons. To work with concave polygons, a convex decomposition would need to be done first. This implies an increase in the run-time and the implementation of a new algorithm that decomposes the concave polygon into convex polygons.
Nesting by a power function: calculating the partial derivatives in the X and Y axes, you could get the escape direction you should take a polygon so that there is a collision between the two polygons. This function of energy and I tested and the three major problems that I have encountered are: first obtaining local minima , second nesting when the collision occurs over a piece and finally the execution time is very high.
Using no-fit polygon: use the no-fit polygon to the nesting can be somewhat interesting. I have read several papers on the subject although there are very few online documentation on it. Not sure if it can really be a useful choice. I still have several doubts on the details of this approach.
Any idea which of these algorithms to choose? Or if you know any other options that can be used? I'm a little confused :-) .
Thank you very much.