I haven't done much research on this yet, but i'm just asking around in case this has been done before.
Here's my problem:
I have a set of cubes of an arbitrary height, width and depth. These are either filled or empty. What i'm looking to do is develop an algorithm that is going to create an optimal mesh for this set of cubes by combining the faces of neighboring cubes into one.
My current idea is to step through the set 6 times(twice along each axis, once forwards and once back), and look at the set in cross section. Ignoring cubes that won't be visible from the outside, i'd like to build polygonal face for those cubes in that section. At the end of this, i should have (x+y+z)*2 of these faces. Combining them should give me the resulting optimized mesh for the voxel set.
I'm stumped on the triangulation process however.
If you want to create a mesh from voxel data, the most commonly used algorithm is marching cubes. However I suggest you search the net for iso-surface extraction for more advanced methods.
Related
I observed some applications create a geometric structure apparently by just having a set of touch points. Like this example:
I wonder which algorithms can possibly help me to recreate such geometric structures?
UPDATE
In 3D printing, sometimes a support structure is needed:
The need for support is due to collapse of some 3D object regions, i.e. overhangs, while printing. Support structure is supposed to connect overhangs either to print floor or to 3D object itself. The geometric structure shown in the screenshot above is actually a sample support structure.
I am not a specialist in that matter and I may be missing important issues. So here is what I would naively do.
The triangles having a external normal pointing downward will reveal the overhangs. When projected vertically and merged by common edges, they define polygonal regions of the base plane. You first have to build those projected polygons, find their intersections, and order the intersections by Z. (You might also want to consider the facing polygons to take the surface thickness into account).
Now for every intersection polygon, you draw verticals to the one just below. The projections of the verticals might be sampled from a regular grid or elsehow, to tune the density. You might also consider sampling those pillars from the basement continuously to the upper surface, possibly stopping some of them earlier.
The key ingredient in this procedure is a good polygon intersection algorithm.
I got an outline (list of points) for a plane I want to generate. The plane is quite big and I need evenly distributed vertices inside the outline. Each vertex has a color value from red to green to visualize some data in the plane. I need to visualize the data as precise as possible in real time.
My idea was to simply create a grid and adjust all the vertices outside of the outline. This turned out to be quite complex.
This is a quick example what I want to achieve.
Is there any algorithm that solves this problem?
Is there another way to generate a mesh from an outline with evenly distributed vertices?
It sounds like you want to do something like this:
1) First generate a triangulate your polygon to create a mesh. There are plenty of options: https://en.wikipedia.org/wiki/Polygon_triangulation
2) Then while any of the edges in the mesh are too long (meaning that the points at either end might be too far apart), add the midpoint of the longest edge to the mesh, dividing the adjacent triangles into 2.
The results is a mesh with every point within a limited distance of other points in every direction. The resulting mesh will not necessarily be optimal, in that it may have more points than are strictly required, but it will probably satisfy your needs.
If you need to reduce the number of points and thin triangles, you can apply Delaunay Triangulation flipping around each candidate edge first: https://en.wikipedia.org/wiki/Delaunay_triangulation#Visual_Delaunay_definition:_Flipping
Although not totally clear from the question, the marching cubes algorithm, adapted to two dimensions, comes to mind. A detailed descriptione of the two-dimensional version can be found here.
Delaunay meshing can create evenly distributed vertices inside a shape. The image below shows a combined grid- and Delaunay-mesh. You may have a look here.
I have a program that visualizes triangular meshes and allows the users to draw on the meshes using a pen. I want to have a "snapping" mode in my system. The snapping mode performs drawing corrections for the user in the sense that the user-drawn lines are snapped to the nearest edge (or the silhouette) of that part of the mesh.
I'm looking for an algorithm that compute the edges visible on the mesh from a given point of view. By edges, I'm referring to the outlines of the shape: corner points and the lines between them (similar to the definition of an edge in computer vision/image processing -- such as Canny edges).
So far I've thought of two approaches for this:
Edge detection: so far I've only found this paper. Their method is understandable, yet the implementation is not trivial (due to tensor computations and some ambiguity in their explanations). The problem with this approach is that it produces "edge strength values" which is a value in the range [0, 1] for every vertex. The value of 1 indicates an edge vertex with a high confidence. This introduces extra thresholding parameters in the system which I'd rather not have. Their output looks like this (range [0, 1] scaled to [0, 65535]):
Rendering or non-photorealistic methods such as the one asked in this question or this paper. They seem to be able to create the silhouette that I'm after as can be seen below:
I'm not a graphics expert and as of yet I don't know whether their methods can be used for computation of the feature lines rather than rendering.
I was wondering if anybody has any ideas about a good algorithm for what I want to do. Since the system is very interactive, the performance is important. The snapping feature does not have to be enabled all the time (therefore, if the method is computationally expensive, some delay in when "snapping enabled" mode is toggled can be tolerated while the algorithm is computing the edges.) Also, if you know of any implementation (preferably open source), I'd be grateful if you could share it with me.
There are two types of edges that you want to detect:
silhouette edges are viewpoint dependent, they correspond to the places where the line of sight tangents the surfaces. With a triangulated model, they are easy to determine, as they are shared by a front-facing triangle and a back-facing one.
"angular" edges are viewpoint independent and formed by a discontinuity in the tangent plane direction. As a triangulated model has itself this kind of discontinuity, there is no exact criterion to find them. Just set a threshold on the angle formed by two triangles. This threshold must be such that smooth patches do not trigger.
By this approach, you will find the wanted edges in 3D.
This is not enough, as part of them are hidden by other surfaces. You have the option of integrating them as edges in the 3D model and letting the rendering engine do its job, or, if you have the courage, to implement an hidden lines removal algorithm. (The wikipedia link is a little terse.)
Since posting the question, something else came into my head. Since 2D edge detection is a very well-studied problem, one way of tackling the problem is performing 2D edge detection on the projection image of the mesh.
In other words, given a specific view of the mesh, one could generate a 2D image. A 2D edge detection algorithm (such as Canny edge detector) could then be run on the 2D image and the results can be back-projected to 3D to determine the silhouettes of the mesh in question. One possible advantage of this is simplicity!
Edit (2017):
Even though I moved away from this, I returned to this problem again for a different purpose. To anybody else looking into this problem: there is a paper that talks about various contours from meshes that's worth reading (the paper is "Suggestive Contours for Conveying Shape" by DeCarlo et al.).
Working implementation of the methods discussed in the paper are available here.
I am new to the WebGL and shaders world, and I was wondering what the best way for me to paint only the pixels within a path. I have the positions 2d of each point and I would like to fill with a color inside the path.
2D Positions
Fill
Could someone give me a direction? Thanks!
Unlike the canvas 2d API to do this in WebGL requires you to triangulate the path. WebGL only draws points (squares), lines, and triangles. Everything else (circles, paths, 3d models) is up to you to creatively use those 3 primitives.
In your case you need turn your path into a set of triangles. There are tons of algorithms to do that. Each one has tradeoffs, some only handle convex paths, some don't handle holes, some add more points in the middle and some don't. Some are faster than others. There are also libraries that do it like this one for example
It's kind of a big topic arguably too big to go into detail here. Other SO questions about it already have answers.
Once you do have the path turned into triangles then it's pretty straightforward to pass those triangles into WebGL and have them drawn.
Plenty of answers on SO already cover that as well. Examples
Drawing parametric shapes in webGL (without three.js)
Or you might prefer some tutorials
There is a simple triangulation (mesh generation) for your case. First sort all your vertices into CCW order. Then calculate the middle point of all vertices. Then iterate over your sorted vertices, and push a triangle made of the middle point, the point at vertices[index] and the point at vertices[index+1] to the mesh.
What would be an efficient approach for constraining an object so that it's always at least partially intersecting the view frustum?
The use case is that when viewing a model I want to clamp camera panning, as well as model translation, so that the view frustum is never looking at empty space.
One approach I tried was to wrap the model objects in bounding volumes, then enforce the constraint when those fall outside the frustum. I've tried bounding boxes so far, but am considering using a minimal convex hull.
The problem is that that when you zoom in close enough, it's still possible to be looking at empty space within the boundary, as shown in the attached diagram.
This is for a WebGL application, so needs to be fairly efficient in JavaScript, and also for thousand of vertices.
Ideally you would have a aabb tree of your mesh, and then you can recursively project on camea/screen until you get an intersection ?
http://www.codersnotes.com/algorithms/projected-area-of-an-aabb
edit: it's just frustum culling algo against aabtree does anyway, so looking for optimized solution, is looking for optimized frustum culling things
https://fgiesen.wordpress.com/2010/10/17/view-frustum-culling/
http://www2.in.tu-clausthal.de/~zach/teaching/cg_literatur/vfc_bbox.pdf
As general approximation is possible I would try the point cloud. First create a list of points - either by every Nth mesh vertex or every Nth face centre. With N being for example 10. Once you have this point array all you do is check if any of points is in frustum while updating its orientation. If not then this means that user moved or rotated the camera too much and you need to restore last acceptable orientation.
I know that this may seem quite ridiculous but I think that it is fairly easy to implement and frustum checking of vertex is just couple of multiplications per plane. It will be not perfect though.
You can also make frustum a little smaller to ensure that there is some border around the object.