Rotate all points to align with a vector - vector

I have a vector v = (x,y,z), and I want to rotate all points such that the point (x,y,z) = (0,0,sqrt(x^2 + y^2 + z^2). In other words, I want to make the direction of the vector v be the z axis, and rotate all points such that this is true.
I want the point (1,1,0) to go to (0,0,sqrt(2)), and the point (0,0,1) to go to (-1/(sqrt(2)),-1/sqrt(2),0) given a v of (1,1,0).
I am working in unity3d's left handed axis system, where y is vertical.
My current method is this, using with v = (vx,vy,vz) and x,y,z being the point to be rotated.
float vx = 1;
float vy = 1;
float vz = 0;
float c1 = -vz/(sqrt(vx*vx + vz*vz));
float c2 = -sqrt(vx*vx + vz*vz)/sqrt(vx*vx + vy*vy + vz*vz);
float s1 = -vx/(sqrt(vx*vx + vz*vz));
float s2 = -vy/sqrt(vx*vx + vy*vy + vz*vz);
float rx = x * c1 + y*s1*s2 - z*s1*c2;
float ry = x * 0 + y*c2 + z * s2;
float rz = x * s1 - y*s2*c1 + z*c1*c2;

You are looking for a 3x3 Matrix f with fv=(0,0,1), |x|=|fx|; this needs
( t1 t2 t3 )
f = ( u1 u2 u3 )
( w1 w2 w3 )
where w := v / |v|, and t, u, w are pairwise orthogonal and |t|=|u|=|w|=1.
Chosing t and u depends on what you want to do, but if you just need any t and u, get some via the 3d cross product.

I found the answer, find axis of rotation by taking cross product of (0,0,1) then use this as the axis of rotation with the angle being the angle between the vector (0,0,1) and (vx,vy,vz).
http://en.wikipedia.org/wiki/Rotation_matrix#Rotation_matrix_from_axis_and_angle

Related

Minimum distance between two circles along a specified vector on a cartesian plane

I am trying to solve the following problem (I am using Matlab, though pseudo-code / solutions in other languages are welcome):
I have two circles on a Cartesian plane defined by their centroids (p1, p2) and their radii (r1, r2). circle 1 (c1 = [p1 r1]) is considered 'dynamic': it is being translated along the vector V = [0 -1]. circle 2 (c2 = [p2 r2]) is considered 'static': it lies in the path of c1 but the x component of its centroid is offset from the x component of c2 (otherwise the solution would be trivial: the distance between the circle centroids minus the sum of their radii).
I am trying to locate the distance (d) along V at which circle 1 will 'collide' with circle 2 (see the linked image). I am sure that I can solve this iteratively (i.e. translate c1 to the bounding box of c2 then converge / test for intersection). However, I would like to know if there is a closed form solution to this problem.
Shift coordinates to simplify expressions
px = p1.x - p2.x
py = p1.y - p2.y
And solve quadratic equation for d (zero, one, or two solutions)
px^2 + (py - d)^2 = (r1 + r2)^2
(py - d)^2 = (r1 + r2)^2 - px^2
d = py +/- Sqrt((r1 + r2)^2 - px^2)
That's all.
As the question title does not match the question and accepted answer which is dependent on a fixed vector {0, -1}, or {0, 1} rather than an arbitrary vector I have added another solution that works for any unit vector.
Where (See diagram 1)
dx, dy is the unit vector of travel for circle c1
p1, p2 the centers of the moving circle c1 and static circle c2
r1, r2 the radius of each circle
The following will set d to the distance c1 must travel along dx, dy to collide with c2 if no collision the d will be set to Infinity
There are three cases when there is no solution
The moving circle is moving away from the static circle. u < 0
The moving circle never gets close enough to collide. dSq > rSq
The two circles are already overlapping. u < 0 luckily the math makes
this the same condition as moving away.
Note that if you ignore the sign of u (1 and 3) then d will be the distance to first (causal) contact going backward in time
Thus the pseudo code to find d
d = Infinity
rSq = (r1 + r2) ^ 2
u = (p1.x - p2.x) * dx + (p1.x - p2.x) * dy
if u >= 0
dSq = ((p2.x + dx * u) - p1.x) ^ 2 + ((p2.y + dy * u) - p1.y) ^ 2
if dSq <= rSq
d = u - (rSq - dSq) ^ 0.5
The point of contact can be found with
cpx = p1.x + dx * d;
cpy = p1.x + dy * d;
Diagram 1

Rotation About an Arbitrary Axis in 3 Dimensions Using Matrix

I come accross a math problem about Interactive Computer Graphics.
I summarize and abstract this problem as follows:
I'm going to rotation a 3d coordinate P(x1,y1,z1) around a point O(x0,y0,z0)
and there are 2 vectors u and v which we already know.
u is the direction to O before transformation.
v is the direction to O after transformation.
I want to know how to conduct the calculation and get the coordinate of Q
Thanks a lot.
Solution:
Rotation About an Arbitrary Axis in 3 Dimensions using the following matrix:
rotation axis vector (normalized): (u,v,w)
position coordinate of the rotation center: (a,b,c)
rotation angel: theta
Reference:
https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnxnbGVubm11cnJheXxneDoyMTJiZTZlNzVlMjFiZTFi
for just single point no rotations is needed ... so knowns are:
u,v,O,P
so we now the distance is not changing:
|P-O| = |Q-O|
and directions are parallel to u,v so:
Q = O + v*(|P-O|/|v|)
But I suspect you want to construct rotation (transform matrix) such that more points (mesh perhaps) are transformed. If that is true then you need at least one known to get this right. Because there is infinite possible rotations transforming P -> Q but the rest of the mesh will be different for each ... so you need to know at least 2 non trivial points pair P0,P1 -> Q0,Q1 or axis of rotation or plane parallel to rotation or any other data known ...
Anyway in current state you can use as rotation axis vector perpendicular to u,v and angle obtained from dot product:
axis = cross (u,v)
ang = +/-acos(dot(u,v))
You just need to find out the sign of angle so try both and use the one for which the resultinq Q is where it should be so dot(Q-O,v) is max. To rotate around arbitrary axis and point use:
Rodrigues_rotation_formula
Also this might be helpfull:
Understanding 4x4 homogenous transform matrices
By computing dot product between v and u get the angle l between the vectors. Do a cross product of v and u (normalized) to produce axis of rotation vector a. Let w be a vector along vector u from O to P. To rotate point P into Q apply the following actions (in pseudo code) having axis a and angle l computed above:
float4 Rotate(float4 w, float l, float4 a)
{
float4x4 Mr = IDENTITY;
quat_t quat = IDENTITY;
float4 t = ZERO;
float xx, yy, zz, xy, xz, yz, wx, wy, wz;
quat[X] = a[X] * sin((-l / 2.0f));
quat[Y] = a[Y] * sin((-l / 2.0f));
quat[Z] = a[Z] * sin((-l / 2.0f));
quat[W] = cos((-l / 2.0f));
xx = quat[X] * quat[X];
yy = quat[Y] * quat[Y];
zz = quat[Z] * quat[Z];
xy = quat[X] * quat[Y];
xz = quat[X] * quat[Z];
yz = quat[Y] * quat[Z];
wx = quat[W] * quat[X];
wy = quat[W] * quat[Y];
wz = quat[W] * quat[Z];
Mr[0][0] = 1.0f - 2.0f * (yy + zz);
Mr[0][1] = 2.0f * (xy + wz);
Mr[0][2] = 2.0f * (xz - wy);
Mr[0][3] = 0.0f;
Mr[1][0] = 2.0f * (xy - wz);
Mr[1][1] = 1.0f - 2.0f * (xx + zz);
Mr[1][2] = 2.0f * (yz + wx);
Mr[1][3] = 0.0f;
Mr[2][0] = 2.0f * (xz + wy);
Mr[2][1] = 2.0f * (yz - wx);
Mr[2][2] = 1.0f - 2.0f * (xx + yy);
Mr[2][3] = 0.0f;
Mr[3][0] = 0.0f;
Mr[3][1] = 0.0f;
Mr[3][2] = 0.0f;
Mr[3][3] = 1.0f;
w = Mr * w;
return w;
}
Point Q is at the end of the rotated vector w. Algorithm used in the pseudo code is quaternion rotation.
If you know u, v, P, and O then I would suggest that you compute |OP| which should be preserved under rotations. Then multiply this length by the unit vector -v (I assumed u, v are unit vectors: if not - normalize them) and translate the origin by this -|OP|v vector. The negative sign in front of v comes from the description given in your question:"v is the direction to O after transformation".
P and Q are at the same distance R to O
R = sqrt( (x1-x0)^2 + (y1-y0)^2 + (z1-z0)^2 )
and OQ is collinear to v, so OQ = v * R / ||v|| where ||v|| is the norm of v
||v|| = sqrt( xv^2 + yv^2 + zv^2 )
So the coordinates of Q(xq,yq,zq) are:
xq= xo + xv * R / ||v||
yq= yo + yv * R / ||v||
zq= zo + zv * R / ||v||

How to calculate coordinates of third point in a triangle (2D) knowing 2 points coordinates, all lenghts and all angles [closed]

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I have a triangle and I know the coordinates of two vertices: A=(x1,y1),B=(x2,y2)
All the angles: ABC=90∘,CAB=30∘ and BCA=60∘ and all the edge lengths. How can I find the coordinates of the third vertex C=(x3,y3)?
I know there are two solutions (I want both).
You know p1 and p2. You know the internal angles.
Make a ray from p1 trough p2, and rotate it CW or CCW 30° around p1.
Make a line trough p1 and p2, and rotate it 90° around p2.
Calculate the intersections.
You get the points:
x3 = x2 + s*(y1 - y2)
y3 = y2 + s*(x2 - x1)
and
x3 = x2 + s*(y2 - y1)
y3 = y2 + s*(x1 - x2)
where s = 1/sqrt(3) ≈ 0.577350269
In a 30-60-90 right triangle, smallest leg (the smallest side adjacent the 90 degree angle) has length of 1/2 of the hypotenuse (the side opposite to 90 degree angle), so since you have the side lengths, you can determine which leg is the line segment AB.
From that you deduce where do the angles go.
Then to compute the coordinate you just need to pick the point on the circle of the radius with the correct radius length at the correct angle.
Two solutions come from measuring the angle clock-wise or counter-clockwise, and result in symmetrical triangles, with the edge AB being the line of symmetry.
Since you already have given the angles, compute the length of AB via quadratic formula
L(AB) = Sqrt[(x1-x2)^2 + (y1-y2)^2].
Now, let x = L(AC) = 2*L(BC) so since it is the right triangle,
L(AC)^2 = L(BC)^2 + L(AB)^2,
x^2 = (0.5x)^2 + L(AB)^2, so L(AB) = x*Sqrt[3]/2,
and since you already computed L(AB) you now have x.
The angle of the original AB is a = arctan([y2-y1]/[x2-x1]).
Now you can measure 30 degrees up or down (use a+30 or a-30 as desired)
and mark the point C on the circle (centered at A) of radius x (which we computed above) at the angle a +/- 30.
Then, C has coordinates
x3 = x1 + x*cos(a+30)
y3 = y1 + x*sin(a+30)
or you can use (a-30) to get the symmetrical triangle.
Here is the code to return points of full polygon if two points and number of sides are provided as input.
This is written for Android(Java) and the logic can be re-used for other languages
private static final float angleBetweenPoints(PointF a, PointF b) {
float deltaY = b.y - a.y;
float deltaX = b.x - a.x;
return (float) (Math.atan2(deltaY, deltaX));
}
private static PointF pullPointReferenceToLineWithAngle(PointF a, PointF b,
float angle) {
float angleBetween = angleBetweenPoints(b, a);
float distance = (float) Math.hypot(b.x - a.x, b.y - a.y);
float x = (float) (b.x + (distance * Math.cos((angleBetween + angle))));
float y = (float) (b.y + (distance * Math.sin((angleBetween + angle))));
return new PointF(x, y);
}
private static List<PointF> pullPolygonPointsFromBasePoints(PointF a,
PointF b, int noOfSides) {
List<PointF> points = new ArrayList<>();
points.add(a);
points.add(b);
if (noOfSides < 3) {
return points;
}
float angleBetweenTwoSides = (float) ((((noOfSides - 2) * 180) / noOfSides)
* Math.PI / 180);
for (int i = 3; i <= noOfSides; i++) {
PointF nextPoint = pullPointReferenceToLineWithAngle(
points.get(i - 3), points.get(i - 2), angleBetweenTwoSides);
points.add(nextPoint);
}
return points;
}
Usage is onDraw method:
PointF a = new PointF(100, 600);
PointF b = new PointF(300, 500);
int noOfSides = 3;
List<PointF> polygonPoints = pullPolygonPointsFromBasePoints(a, b,
noOfSides);
drawPolyPoints(canvas, noOfSides, polygonPoints);
This is a right angled triangle. The angle ABC is 90 degrees, so calculate the vector joining A to B and call this AA and normalise it:
AA = (x2-x1,y2-y1) / |(x2-x1,y2-y1)|
A unit vector perpendicular to AA is given by
BB = (-(y2-y1),x2-x1) / |(x2-x1,y2-y1)|
Because AC is perpendicular to AB all you can obtain your first point P1 as
P1 = (x2,y2) + K * BB
where K is the scalar value equal to the length of side AC (which you say you already know in the question). Your second solution point P2 is then simply given by going in the negative BB direction
P2 = (x2,y2) - K * BB

Computing the 3D coordinates on a unit sphere from a 2D point

I have a square bitmap of a circle and I want to compute the normals of all the pixels in that circle as if it were a sphere of radius 1:
The sphere/circle is centered in the bitmap.
What is the equation for this?
Don't know much about how people program 3D stuff, so I'll just give the pure math and hope it's useful.
Sphere of radius 1, centered on origin, is the set of points satisfying:
x2 + y2 + z2 = 1
We want the 3D coordinates of a point on the sphere where x and y are known. So, just solve for z:
z = ±sqrt(1 - x2 - y2).
Now, let us consider a unit vector pointing outward from the sphere. It's a unit sphere, so we can just use the vector from the origin to (x, y, z), which is, of course, <x, y, z>.
Now we want the equation of a plane tangent to the sphere at (x, y, z), but this will be using its own x, y, and z variables, so instead I'll make it tangent to the sphere at (x0, y0, z0). This is simply:
x0x + y0y + z0z = 1
Hope this helps.
(OP):
you mean something like:
const int R = 31, SZ = power_of_two(R*2);
std::vector<vec4_t> p;
for(int y=0; y<SZ; y++) {
for(int x=0; x<SZ; x++) {
const float rx = (float)(x-R)/R, ry = (float)(y-R)/R;
if(rx*rx+ry*ry > 1) { // outside sphere
p.push_back(vec4_t(0,0,0,0));
} else {
vec3_t normal(rx,sqrt(1.-rx*rx-ry*ry),ry);
p.push_back(vec4_t(normal,1));
}
}
}
It does make a nice spherical shading-like shading if I treat the normals as colours and blit it; is it right?
(TZ)
Sorry, I'm not familiar with those aspects of C++. Haven't used the language very much, nor recently.
This formula is often used for "fake-envmapping" effect.
double x = 2.0 * pixel_x / bitmap_size - 1.0;
double y = 2.0 * pixel_y / bitmap_size - 1.0;
double r2 = x*x + y*y;
if (r2 < 1)
{
// Inside the circle
double z = sqrt(1 - r2);
.. here the normal is (x, y, z) ...
}
Obviously you're limited to assuming all the points are on one half of the sphere or similar, because of the missing dimension. Past that, it's pretty simple.
The middle of the circle has a normal facing precisely in or out, perpendicular to the plane the circle is drawn on.
Each point on the edge of the circle is facing away from the middle, and thus you can calculate the normal for that.
For any point between the middle and the edge, you use the distance from the middle, and some simple trig (which eludes me at the moment). A lerp is roughly accurate at some points, but not quite what you need, since it's a curve. Simple curve though, and you know the beginning and end values, so figuring them out should only take a simple equation.
I think I get what you're trying to do: generate a grid of depth data for an image. Sort of like ray-tracing a sphere.
In that case, you want a Ray-Sphere Intersection test:
http://www.siggraph.org/education/materials/HyperGraph/raytrace/rtinter1.htm
Your rays will be simple perpendicular rays, based off your U/V coordinates (times two, since your sphere has a diameter of 2). This will give you the front-facing points on the sphere.
From there, calculate normals as below (point - origin, the radius is already 1 unit).
Ripped off from the link above:
You have to combine two equations:
Ray: R(t) = R0 + t * Rd , t > 0 with R0 = [X0, Y0, Z0] and Rd = [Xd, Yd, Zd]
Sphere: S = the set of points[xs, ys, zs], where (xs - xc)2 + (ys - yc)2 + (zs - zc)2 = Sr2
To do this, calculate your ray (x * pixel / width, y * pixel / width, z: 1), then:
A = Xd^2 + Yd^2 + Zd^2
B = 2 * (Xd * (X0 - Xc) + Yd * (Y0 - Yc) + Zd * (Z0 - Zc))
C = (X0 - Xc)^2 + (Y0 - Yc)^2 + (Z0 - Zc)^2 - Sr^2
Plug into quadratic equation:
t0, t1 = (- B + (B^2 - 4*C)^1/2) / 2
Check discriminant (B^2 - 4*C), and if real root, the intersection is:
Ri = [xi, yi, zi] = [x0 + xd * ti , y0 + yd * ti, z0 + zd * ti]
And the surface normal is:
SN = [(xi - xc)/Sr, (yi - yc)/Sr, (zi - zc)/Sr]
Boiling it all down:
So, since we're talking unit values, and rays that point straight at Z (no x or y component), we can boil down these equations greatly:
Ray:
X0 = 2 * pixelX / width
Y0 = 2 * pixelY / height
Z0 = 0
Xd = 0
Yd = 0
Zd = 1
Sphere:
Xc = 1
Yc = 1
Zc = 1
Factors:
A = 1 (unit ray)
B
= 2 * (0 + 0 + (0 - 1))
= -2 (no x/y component)
C
= (X0 - 1) ^ 2 + (Y0 - 1) ^ 2 + (0 - 1) ^ 2 - 1
= (X0 - 1) ^ 2 + (Y0 - 1) ^ 2
Discriminant
= (-2) ^ 2 - 4 * 1 * C
= 4 - 4 * C
From here:
If discriminant < 0:
Z = ?, Normal = ?
Else:
t = (2 + (discriminant) ^ 1 / 2) / 2
If t < 0 (hopefully never or always the case)
t = -t
Then:
Z: t
Nx: Xi - 1
Ny: Yi - 1
Nz: t - 1
Boiled farther still:
Intuitively it looks like C (X^2 + Y^2) and the square-root are the most prominent figures here. If I had a better recollection of my math (in particular, transformations on exponents of sums), then I'd bet I could derive this down to what Tom Zych gave you. Since I can't, I'll just leave it as above.

Non-axis aligned scaling

Finding a good way to do this has stumped me for a while now: assume I have a selection box with a set of points in it. By dragging the corners you can scale the (distance between) points in the box. Now for an axis aligned box this is easy. Take a corner as an anchor point (subtract this corner from each point, scale it, then add it to the point again) and multiply each points x and y by the factor with which the box has gotten bigger.
But now take a box that is not aligned with the x and y axis. How do you scale the points inside this box when you drag its corners?
Any box is contained inside a circle.
You find the circle which binds the box, find its center and do exactly the same as you do with an axis aligned box.
You pick one corner of the rectangle as the origin. The two edges connected to it will be the basis (u and v, which should be perpendicular to each other). You would need to normalize them first.
Subtract the origin from the coordinates and calculate the dot-product with the scaling vector (u), and with the other vector (v). This would give you how much u and v contributes to the coordinate.
Then you scale the component you want. To get the final coordinate, you just multiply the the (now scaled) components with their respective vector, and add them together.
For example:
Points: p1 = (3,5) and p2 = (6,4)
Selection corners: (0,2),(8,0),(9,4),(1,6)
selected origin = (8,0)
u = ((0,2)-(8,0))/|(0,2)-(8,0)| = <-0.970, 0.242>
v = <-0.242, -0.970>
(v is u, but with flipped coordinates, and one of them negated)
p1´ = p1 - origin = (-5, 5)
p2´ = p2 - origin = (-2, 4)
p1_u = p1´ . u = -0.970 * (-5) + 0.242 * 5 = 6.063
p1_v = p1´ . v = -0.242 * (-5) - 0.970 * 5 = -3.638
Scale p1_u by 0.5: 3.038
p1_u * u + p1_v * v + origin = <5.941, 4.265>
Same for p2: <7.412, 3.647>
As you maybe can see, they have moved towards the line (8,0)-(9,4), since we scaled by 0.5, with (0,8) as the origin.
Edit: This turned out to be a little harder to explain than I anticipated.
In python code, it could look something like this:
def scale(points, origin, u, scale):
# normalize
len_u = (u[0]**2 + u[1]**2) ** 0.5
u = (u[0]/len_u, u[1]/len_u)
# create v
v = (-u[1],u[0])
ret = []
for x,y in points:
# subtract origin
x, y = x - origin[0], y - origin[1]
# calculate dot product
pu = x * u[0] + y * u[1]
pv = x * v[0] + y * v[1]
# scale
pu = pu * scale
# transform back to normal space
x = pu * u[0] + pv * v[0] + origin[0]
y = pu * u[1] + pv * v[1] + origin[1]
ret.append((x,y))
return ret
>>> scale([(3,5),(6,4)],(8,0),(-8,2),0.5)
[(5.9411764705882355, 4.2647058823529411), (7.4117647058823533, 3.6470588235294117)]
Let's say that the box is defined as a set of four points (P1, P2, P3 and P4).
For the sake of simplicity, we'll say you are dragging P1, and that P3 is the opposite corner (the one you are using as an anchor).
Let's label the mouse position as M, and the new points you wish to calculate as N1, N2 and N4. P3 will, of course, remain the same.
Your scaling factor can be simply computed using vector subtraction and the vector dot product:
scale = ((M - P3) dot (P1 - P3)) / ((P1 - P3) dot (P1 - P3))
And the three new points can be found using scalar multiplication and vector addition:
N1 = scale*P1 + (1 - scale)*P3
N2 = scale*P2 + (1 - scale)*P3
N4 = scale*P4 + (1 - scale)*P3
edit: I see that MizardX has answered the question already, so my answer is here to help with that difficult explanation. I hope it helps!
edit: here is the algorithm for non-proportional scaling. In this case, N1 is equal to M (the point being dragged follows the mouse), so the only points of interest are N2 and N4:
N2 = ((M - P3) dot (P2 - P3)) / ((P2 - P3) dot (P2 - P3)) * (P2 - P3) + P3
N4 = ((M - P3) dot (P4 - P3)) / ((P4 - P3) dot (P4 - P3)) * (P4 - P3) + P3
where * represents scalar multiplication
edit: Here is some C++ code which answers the question. I'm sure this question is long-dead by now, but it was an interesting problem, and I had some fun writing the code.
#include <vector>
class Point
{
public:
float x;
float y;
Point() { x = y = 0; }
Point(float nx, float ny) { x = nx; y = ny; }
};
Point& operator-(Point& A, Point& B) { return Point(A.x-B.x, A.y-B.y); }
Point& operator+(Point& A, Point& B) { return Point(A.x+B.x, A.y+B.y); }
Point& operator*(float sc, Point& P) { return Point(sc*P.x, sc*P.y); }
float dot_product(Point A, Point B) { return A.x*B.x + A.y*B.y; }
struct Rect { Point point[4]; };
void scale_points(Rect box, int anchor, Point mouse, vector<Point> points)
{
Point& P3 = box.point[anchor];
Point& P2 = box.point[(anchor + 1)%4];
Point& P1 = box.point[(anchor + 2)%4];
Point& P4 = box.point[(anchor + 3)%4];
Point A = P4 - P3;
Point aFactor = dot_product(mouse - P3, A) / dot_product(A, A) * A;
Point B = P2 - P3;
Point bFactor = dot_product(mouse - P3, B) / dot_product(B, B) * B;
for (int i = 0; i < points.size(); i++)
{
Point P = points[i] - P3;
points[i] = P3 + dot_product(P, aFactor) + dot_product(P, bFactor);
}
}

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