I have an array of CGPoints (basic struct with two floats: x and y). I want to use OpenGL ES to draw a textured curve using these points. I can do this fine with just two points, but it gets harder when I need to make a line from several points.
Currently I draw a line horizontally, calculate its angle from the points given, and then rotate it. I don't think doing this for all lines in a curve is a good idea. There's probably a faster way.
I'm thinking that I can "enlarge" or "constrict" all the points at once to make a curve with some sort of width.
I'm not positive what you want to accomplish, but consider this:
Based on a ordered list of points, you can draw a polyline using those points. If you want to have a polyline with a 2D texture on it, you can draw a series of quadrilaterals (using two triangles each, of course). You can generate these quadrilaterals using an idea similar to catmul-rom spline generation.
Consider a series of points p[i-1], p[i], p[i+1]. Now, for each i, you can find two points each an epsilon distance away from p[i] along the line perpendicular to the line connecting p[i-1] and p[i+1]. You can determine the two points generated for the endpoints in various ways, like using the perpendicular to the line from p[0] to p[1].
I'm not sure if this will be faster than your method, but you should be caching the results. If you are planning on doing this every frame, another type of solution to your problem may be needed.
Related
I have a single mesh game object that is essentially a long line that curves and slopes up/down. What I'm trying to do is generate some text along this line at a specified distance interval. Let's say every 100 units along the line some text should appear. If it was a straight line it would be easy, but the curves and slopes are throwing me off.
I retrieved the vertices that created this mesh by doing:
model.GetComponent<MeshFilter>().mesh.vertices
I then transform them to world-space by looping over them and doing:
meshFilter.gameObject.transform.TransformPoint(vertices[i])
Now, these vertices are NOT evenly spaced. For slopes and curves, there are a lot of vertices. For the straighter parts, there are less. But these straight parts still vary slightly (usually by ~.10 of the Y value). Originally I was looping through and keeping track of the distance to find the vertices closest to the interval, but that was when I thought they were evenly spaced.
Here's part of the model:
I colored all the vertices black here to show how condensed they are at curves/slopes vs ~straight parts:
Here's the inspector for the model just incase:
Do you use a static single mesh?
In your solution, I think the problem is vertices. you have to find vertices along your line and ignore the vertical group of them and its too difficult.
If your mesh may be changed by player, I suggest you to use Trail Render Component, get its vertices and solve a simple Knapsack problem to put your characters (suggest you use TextmeshPro)
I have an .obj file representing a 3D object.
I need to extract from this 3D object the contour that is obtained by intersection with a plane. So for example, I have an object representing a cylinder oriented with vertical axis, then I want to extract a circle contour when the intersecting plane is horizontal or a rectangular contour when the intersection plane is vertical. Any suggestion about how to do it?
Since I didn't know how to visualise this obj file, I have converted to a patch with the following code (some function taken from loadawobj from Matlab file exchange).
modelname='file.obj';
S=loadawobj(modelname);
mtl=loadawmtl(['obj/' S.mtllib]);
p3=patch('Vertices',S.v','Faces',S.f3');
for ii=1:length(S.umat3)
mtlnum=S.umat3(ii);
fvcd3(ii,:)=mtl(1).Kd';
end
p3.FaceVertexCData=fvcd3;
p3.FaceColor='flat';
But I don't necessarily need to extract the contour from the resulting patch if this is too complex to accomplish. If there is an easier procedure starting from the obj file, it's also fine and acceptable. Thank you!
That's the way I solved the problem, after collecting information all around the web. I couldn't find anything ready on line so I had to implement an algorithm on my own. The basic idea is very simple but there are many steps required. I start from two info: one array containing the coordinates of the cloud point and another array containing a bunch of tuples about how the 3 vertex are connected to form a triangle.
First of all you need to find a representation of the plane you want to use for your cutting. That means you just use one point and the normal to the plane to represent it. That plane is required in order to identify the cutting point on the structure.
Second step is to identify the triangles on the plane. In few words you just need to scroll over all the triangles of the structure and find those having one corner above the cutting plane and another corner below the cutting plane. Also don't forget to account for the condition where one corner is on the plane or two are on the plane. All the other triangles are not needed, since they are totally above or below the cutting plane.
Now you have a subset of all your triangles. You need to extract points of the contour. So for each triangle you have 3 vertex: in general case you can imagine that one vertex is above the plane and the other two are below. Then you have two lines cutting the plane. You can extract two point by simply intersecting these lines with the cutting plane.
By repeating this operation you get a series of points on 2D space. But they have no order and if you plot them as a continuous plot, you get lines jumping up and down since the points you have extracted are randomly located in the array. So, it's required to order them in a proper way. The method I used is the very simple: start from one point and connect to the closest one. There are some bad situations where that doesn't work but you can probably avoid it by adding some more rules on the algorithm.
hi i want to detect fingertips point and valleypoint of hand by using hough transform.Simply the Question is what is the [H,theta,rho]=hough(BW) is good for extract these point.
the image is here:
https://www.dropbox.com/sh/n1lz7b5eedzbui7/AADwy5O1l7sWf5aOx7KWAmhOa?dl=0
tnx
The standard hough transformation is just for detecting straight lines. Not more and not less. The Matlab function hough (please see here) returns the so-called hough space H, a parametric space which is used to find these lines and the parametric representation of each line: rho = x*cos(theta) + y*sin(theta).
You will have to do more than this to detect your desired points. Since your fingers usually won't consist of straight lines, I think you should think of something else anyway, e.g. if you can assume such a perfect curve as the one in your image maybe this is interesting for you.
Another simple technique you might consider is to compare the straight line distance between two points on your hand line to the distance between those two points along the perimeter (geodesic distance). For this you would need an ordered list of points along the perimeter.
Along regions of high curvature, the straight line distance between two points will be smaller than the number of pixels between those two points along the perimeter.
For example, you could check perimeter pixels separate by 10 pixels. That is, you would search through the list and compare the point at index N and the point index N+10. (You'll need to loop back around to the beginning of the list as you approach the end.) If the straight line distance between these two points is nearly 10 pixels as well, then you know those points lie on a straight section of the perimeter. If the straight line distance is much smaller than 10, then you know the perimeter curves in some fashion between those points. Whether you check pixels that are 5, 10, 20, or 30 items apart in the list will depend on the resolution of your image and the curves you're looking for.
This technique is useful because it's simple and quick to implement. Maybe it would work well enough for your needs.
Yet another way: simplify the outline to small line segments, and then you can calculate the line-line angle between adjacent segments. To simplify the curves, implement the Ramer-Douglas-Puecker algorithm. A little experimentation will reveal what parameter settings will work for your application.
https://en.wikipedia.org/wiki/Ramer%E2%80%93Douglas%E2%80%93Peucker_algorithm
Finally, you could look into piecewise curve fitting: a curve would be fitted to small segments of the outline. This can get very complicated, and researchers continue to find ways to decompose complex figures into a limited number of more basic shapes or curves. I recommend trying the simplest technique and then only adding complexity if you need it.
I am currently doing some image segmentation on a bone qCT picture, see for instance images below.
I am trying to find the different borders in the picture for instance the outer border separating the bone to the noisy background. In this analysis I am getting a list of points (vec(1,:) containing x values and vex(2,:) containing the y values) in random order.
To get them into order I am using using a block of code which effectively takes the first point vec(1,1),vec(1,2) and then finds the closest point among the rest of the points in the vector. And then repeats.
Now my problem is that I want to smooth the data but how do I do that as the points lie in a circular formation? (I do have the Curve Fitting Toolbox)
Not exactly a smoothing procedure, but a way to simplify your data would be to compute the boundary of the convex hull of the data.
K = convhull(O(1,:), O(2,:));
plot(O(1,K), O(2,K));
You could also consider using alpha shapes if you want more control.
I have a set with 50 points in x,y. I need to draw the smoothest bezier that passes in all points, or in other words, the bezier that will best fit the points.
How do I do that? thanks
I am undergoing a similar problem in 3D. It is slightly easier in 2D because lines will always intersect if not parallel.
Firstly, read up on quadratic bezier curves. Each curve is represented by three points. The line will not pass through the middle point. Thus, your middle point cannot be one of the points you are trying to fit, or it won't go through it.
Instead, the beginning and end point of your quadratic bezier curve must be two consecutive points you want it to pass through. So what is your middle point going to be?
One way of solving this (never tried it myself HENCE it might not look perfect, but Im thinking off the top of my head) is to calculate the tangents from your -1st data point to your 0th data point, and find the intersection between that and the 1st data point to the 2nd data point. Then draw the line between the 0th data point and the 1st data point using this intersection as the middle bezier curve value.
Obviously you may have trouble at the ends of the curves, that may require some inventive thinking to make them look good. (the first point has no -1st point).
Sorry about the lack of diagrams. I would draw one but I'm on an iPad.
Imagine 3-point bezier curve (start-A, middle-B, end-C)
Imagine a straight line from A to C.
Imagine a straight line that is perpendicular to AC and goes through point B.
Those two lines cross in point D.
Bezier curve will go through EXACTLY half way from D to B. In other words if you want bezier curve that goes through 3 points, you must make the second point 2 times further from start and end than the actual second point.