Question:
I need to calculate intersection shape (purple) of plane defined by Ax + By + Cz + D = 0 and frustum defined by 4 rays emitting from corners of rectangle (red arrows). The result shoud be quadrilateral (4 points) and important requirement is that result shape must be in plane's local space. Plane is created with transformation matrix T (planes' normal is vec3(0, 0, 1) in T's space).
Explanation:
This is perspective form of my rectangle projection to another space (transformation / matrix / node). I am able to calculate intersection shape of any rectangle without perspective rays (all rays are parallel) by plane-line intersection algorithm (pseudocode):
Definitions:
// Plane defined by normal (A, B, C) and D
struct Plane { vec3 n; float d; };
// Line defined by 2 points
struct Line { vec3 a, b; };
Intersection:
vec3 PlaneLineIntersection(Plane plane, Line line) {
vec3 ba = normalize(line.b, line.a);
float dotA = dot(plane.n, l.a);
float dotBA = dot(plane.n, ba);
float t = (plane.d - dotA) / dotBA;
return line.a + ba * t;
}
Perspective form comes with some problems, because some of rays could be parallel with plane (intersection point is in infinite) or final shape is self-intersecting. Its works in some cases, but it's not enough for arbitary transformation. How to get correct intersection part of plane wtih perspective?
Simply, I need to get visible part of arbitary plane by arbitary perspective "camera".
Thank you for suggestions.
Intersection between a plane (one Ax+By+Cx+D equation) and a line (two planes equations) is a matter of solving the 3x3 matrix for x,y,z.
Doing all calculations on T-space (origin is at the top of the pyramid) is easier as some A,B,C are 0.
What I don't know if you are aware of is that perspective is a kind of projection that distorts the z ("depth", far from the origin). So if the plane that contains the rectangle is not perpendicular to the axis of the fustrum (z-axis) then it's not a rectangle when projected into the plane, but a trapezoid.
Anyhow, using the projection perspective matrix you can get projected coordinates for the four rectangle corners.
To tell if a point is in one side of a plane or in the other just put the point coordinates in the plane equation and get the sign, as shown here
Your question seems inherently mathematic so excuse my mathematical solution on StackOverflow. If your four arrows emit from a single point and the formed side planes share a common angle, then you are looking for a solution to the frustum projection problem. Your requirements simplify the problem quite a bit because you define the plane with a normal, not two bounded vectors, thus if you agree to the definitions...
then I can provide you with the mathematical solution here (Internet Explorer .mht file, possibly requiring modern Windows OS). If you are thinking about an actual implementation then I can only direct you to a very similar frustum projection implementation that I have implemented/uploaded here (Lua): https://github.com/quiret/mta_lua_3d_math
The roadmap for the implementation could be as follows: creation of condition container classes for all sub-problems (0 < k1*a1 + k2, etc) plus the and/or chains, writing algorithms for the comparisions across and-chains as well as normal-form creation, optimization of object construction/memory allocation. Since each check for frustum intersection requires just a fixed amount of algebraic objects you can implement an efficient cache.
Related
Does the technique that vulkan uses (and I assume other graphics libraries too) to interpolate vertex attributes in a perspective-correct manner require that the vertex shader must normalize the homogenous camera-space vertex position (ie: divide through by the w-coordinate such that the w-coordinate is 1.0) prior to multiplication by a typical projection matrix of the form...
g/s 0 0 0
0 g 0 n
0 0 f/(f-n) -nf/(f-n)
0 0 1 0
...in order for perspective-correctness to work properly?
Or, will perspective-correctness continue to work on any homogeneous vertex position in camera-space (with a w-coordinate other than 1.0)?
(I didn't completely follow the perspective-correctness math, so it is unclear which to me which is the case.)
Update:
In order to clarify terminology:
vec4 modelCoordinates = vec4(x_in, y_in, z_in, 1);
mat4 modelToWorld = ...;
vec4 worldCoordinates = modelToWorld * modelCoordinates;
mat4 worldToCamera = ...;
vec4 cameraCoordinates = worldToCamera * worldCoordinates;
mat4 cameraToProjection = ...;
vec4 clipCoordinates = cameraToProjection * cameraCoordinates;
output(clipCoordinates);
cameraToProjection is a matrix like the one shown in the question
The question is does cameraCoordinates.w have to be 1.0?
And consequently the last row of both the modelToWorld and worldToCamera matricies have to be 0 0 0 1?
You have this exactly backwards. Doing the perspective divide in the shader is what prevents perspective-correct interpolation. The rasterizer needs the perspective information provided by the W component to do its job. With a W of 1, the interpolation is done in window space, without any regard to perspective.
Provide a clip-space coordinate to the output of your vertex processing stage, and let the system do what it exists to do.
the vertex shader must normalize the homogenous camera-space vertex position (ie: divide through by the w-coordinate such that the w-coordinate is 1.0) prior to multiplication by a typical projection matrix of the form...
If your camera-space vertex position does not have a W of 1.0, then one of two things has happened:
You are deliberately operating in a post-projection world space or some similar construct. This is a perfectly valid thing to do, and the math for a camera space can be perfectly reasonable.
Your code is broken somewhere. That is, you intend for your world and camera space to be a normal, Euclidean, non-homogeneous space, but somehow the math didn't work out. Obviously, this is not a perfectly valid thing to do.
In both cases, dividing by W is the wrong thing to do. If your world space that you're placing a camera into is post-projection (such as in this example), dividing by W will break your perspective-correct interpolation, as outlined above. If your code is broken, dividing by W will merely mask the actual problem; better to fix your code than to hide the bug, as it may crop up elsewhere.
To see whether or not the camera coordinates need to be in normal form, let's represent the camera coordinates as multiples of w, so they are (wx,wy,wz,w).
Multiplying through by the given projection matrix, we get the clip coordinates (wxg/s, wyg, fwz/(f-n)-nfw/(f-n)), wz)
Calculating the x-y framebuffer coordinates as per the fixed Vulkan formula we get (P_x * xg/sz +O_x, P_y * Hgy/z + O_y). Notice this does not depend on w, so the position in the framebuffer of a polygons verticies doesn't require the camera coordinates be in normal form.
Likewise calculation of the barycentric coordinates of fragments within a polygon only depends on x,y in framebuffer coordinates, and so is also independant of w.
However perspective-correct perspective interpolation of fragment attributes does depend on W_clip of the verticies as this is used in the formula given in the Vulkan spec. As shown above W_clip is wz which does depend on w and scales with it, so we can conclude that camera coordinates must be in normal form (their w must be 1.0)
I need to offset a curve, which by the simplest way is just shifting the points perpendicularly. I can access each point to calculate angle of each line along given path, for now I use atan2. Then I take those two angle and make average of it. It returns the shortest angle, not what I need in this case.
How can I calculate angle of each connection? Concerning that I am not interested in the shortest angle but the one that would create parallel offset curve.
Assuming 2D case...
So do a cross product of direction vectors of 2 neighboring lines the sign of z coordinate of the result will tell you if the lines are CW/CCW
So if you got 3 consequent control points on the polyline: p0,p1,p2 then:
d1 = p1-p0
d2 = p2-p1
if you use some 3D vector math then convert them to 3D by setting:
d1.z=0;
d2.z=0;
now compute 3D cross:
n = cross(d1,d2)
which returns vector perpendicular to both vectors of size equals to the area of quad (parallelogram) constructed with d1,d2 as base vectors. The direction (from the 2 possible) is determined by the winding rule of the p0,p1,p2 so inspecting z of the result is enough.
The n.x,n.y are not needed so you can compute directly without doing full cross product:
n.z=(d1.x*d2.y)-(d1.y*d2.x)
if (n.z>0) case1
if (n.z<0) case2
if the case1 is CW or CCW depends on your coordinate system properties (left/right handness). This approach is very commonly used in CG fur back face culling of polygons ...
if n.z is zero it means that your vectors/lines are either parallel or at lest one of them is zero.
I think these might interest you:
draw outline for some connected lines
How can I create an internal spiral for a polygon?
Also in 2D you do not need atan2 to get perpendicular vector... You can do instead this:
u = (x,y)
v = (-y,x)
w = (x,-y)
so u is any 2D vector and v,w are the 2 possible perpendicular vectors to u in 2D. they are the result of:
cross((x,y,0),(0,0,1))
cross((0,0,1),(x,y,0))
I'm trying to find the best way to calculate this. On a 2D plane I have fixed points all with an instantaneous measurement value. The coordinates of these points is known. I want to predict the value of a movable point between these fixed points. The movable point coodinates will be known. So the distance betwwen the points is known as well.
This could be comparable to temperature readings or elevation on topography. I this case I'm wanting to predict ionospheric TEC of the mobile point from the fixed point measurements. The fixed point measurements are smoothed over time however I do not want to have to store previous values of the mobile point estimate in RAM.
Would some sort of gradient function be the way to go here?
This is the same algorithm for interpolating the height of a point from a triangle.
In your case you don't have z values for heights, but some other float value for each triangle vertex, but it's the same concept, still 3D points.
Where you have 3D triangle points p, q, r and test point pt, then pseudo code from the above mathgem is something like this:
Vector3 v1 = q - p;
Vector3 v2 = r - p;
Vector3 n = v1.CrossProduct(v2);
if n.z is not zero
return ((n.x * (pt.x - p.x) + n.y * (pt.y - p.y)) / -n.z) + p.z
As you indicate in your comment to #Phpdevpad, you do have 3 fixed points so this will work.
You can try contour plots especially contour lines. Simply use a delaunay triangulation of the points and a linear transformation along the edges. You can try my PHP implementations https://contourplot.codeplex.com for geographic maps. Another algorithm is conrec algorithm from Paul Bourke.
I'm trying to find the best way to get the most distant point of a circle from a specified point in 2D space. What I have found so far, is how to get the distance between the point and the circle position, but I'm not entirely sure how to expand this to find the most distant point of the circle.
The known variables are:
Point a
Point b (circle position)
Radius r (circle radius)
To find the distance between the point and the circle position, I have found this:
xd = x2 - x1
yd = y2 - y1
Distance = SquareRoot(xd * xd + yd * yd)
It seems to me, this is part of the solution. How would this be expanded to get the position of Point x in the below image?
As an additional but optional part of the question: I have read in some places that it would be possible to get the distance portion without using the Square Root, which is very performance intensive and should be avoided if fast code is necessary. In my case, I would be doing this calculation quite often; Any comments on this within the context of the main question would be welcome too.
What about this?
Calculate A-B.
We now have a vector pointing from the center of the circle towards A (if B is the origin, skip this and just consider point A a vector).
Normalize.
Now we have a well defined length (the length is 1)
If the circle is not of unit radius, multiply by radius. If it is unit radius, skip this.
Now we have the correct length.
Invert sign (can be done in one step with 3., just multiply with the negative radius)
Now our vector points in the correct direction.
Add B (if B is the origin, skip this).
Now our vector is offset correctly so its endpoint is the point we want.
(Alternatively, you could calculate B-A to save the negation, but then you have to do one more operation to offset the origin correctly.)
By the way, it works the same in 3D, except the circle would be a sphere, and the vectors would have 3 components (or 4, if you use homogenous coords, in this case remember -- for correctness -- setting w to 0 when "turning points into vectors" and to 1 at the end when making a point from the vector).
EDIT:
(in reply of pseudocode)
Assuming you have a vec2 class which is a struct of two float numbers with operators for vector subtraction and scalar multiplicaion (pretty trivial, around a dozen lines of code) and a function normalize which needs to be no more than a shorthand for multiplying with inv_sqrt(x*x+y*y), the pseudocode (my pseudocode here is something like a C++/GLSL mix) could look something like this:
vec2 most_distant_on_circle(vec2 const& B, float r, vec2 const& A)
{
vec2 P(A - B);
normalize(P);
return -r * P + B;
}
Most math libraries that you'd use should have all of these functions and types built-in. HLSL and GLSL have them as first type primitives and intrinsic functions. Some GPUs even have a dedicated normalize instruction.
I am trying to design an asic graphics processor. I have done extensive research on the topic but I am still kind of fuzzy on how to translate and rotate points. I am using orthographic projection to rasterize the transformed points.
I have been using the following lecture regarding the matrix multiplication (homogenous coordinates)
http://www.cs.kent.edu/~zhao/gpu/lectures/Transformation.pdf
Could someone please explain this a little more in depth to me. I am still somewhat shakey on the algorithm. I am passing a camera (x,y,z) and a camera vector (x,y,z) representing the camera angle, along with a point (x,y,z). What should go where within the matrices to transform the point to the new appropriate location?
Here's the complete transformation algorithm in pseudocode:
void project(Vec3d objPos, Matrix4d modelViewMatrix,
Matrix4d projMatrix, Rect viewport, Vec3d& winCoords)
{
Vec4d in(objPos.x, objPos.y, objPos.z, 1.0);
in = projMatrix * modelViewMatrix * in;
in /= in.w; // perspective division
// "in" is now in normalized device coordinates, which are in the range [-1, 1].
// Map coordinates to range [0, 1]
in.x = in.x / 2 + 0.5;
in.y = in.y / 2 + 0.5;
in.z = in.z / 2 + 0.5;
// Map to viewport
winCoords.x = in.x * viewport.w + viewport.x;
winCoords.y = in.y * viewport.h + viewport.y;
winCoords.z = in.z;
}
Then rasterize using winCoords.x and winCoords.y.
For an explanation of the stages of this algorithm, see question 9.011 from the OpenGL FAQ.
For the first few years they were for sale, mass-market graphics processors for PC didn't translate or rotate points at all. Are you required to implement this feature? If not, you may wish to let software do it. Depending on your circumstances, software may be the more sensible route.
If you are required to implement the feature, I'll tell you how they did it in the early days.
The hardware has sixteen floating point registers that represent a 4x4 matrix. The application developer loads these registers with the ModelViewProjection matrix just before rendering a mesh of triangles. The ModelViewProjection matrix is:
Model * View * Projection
Where "Model" is a matrix that brings vertices from "model" coordinates into "world" coordinates, "View" is a matrix that brings vertices from "world" coordinates into "camera" coordinates, and "Projection" is a matrix that brings vertices from "camera" coordinates to "screen" coordinates. Together they bring vertices from "model" coordinates - coordinates relative to the 3D model they belong to - into "screen" coordinates, where you intend to rasterize them as triangles.
Those are three different matrices, but they're multiplied together and the 4x4 result is written to hardware registers.
When a buffer of vertices is to be rendered as triangles, the hardware reads in vertices as [x,y,z] vectors from memory, and treats them as if they were [x,y,z,w] where w is always 1. It then multiplies each vector by the 4x4 ModelViewProjection matrix to get [x',y',z',w']. If there is perspective (you said there wasn't) then we divide by w' to get perspective [x'/w',y'/w',z'/w',w'/w'].
Then triangles are rasterized with the newly computed vertices. This enables a model's vertices to be in read-only memory if desired, though the model and camera may be in motion.