A quadratic bezier curve needs these three points, but I do not have an ordered pair of p1. Instead, I have the ordered pair of points here
The middle point (P1) is the highest point of the parabola.
The parabola is equal in both sides
How do I get the 3 points from image 1 using the points from image 2?
Apply the knowledge explained in https://pomax.github.io/bezierinfo/#abc and you should be good to go. You'll need to decide which time value that "somewhere on the curve" point has, and then you can use the formula for the projection ratio to find the actual control point coordinate.
However, at t=0.5 the ratio is just "1:1" so things get even easier because your point projects onto the midpoint of the line that connects that first and last point, and the real control point is the same distance "above" your point as the point is above that line:
So you just compute the midpoint:
m =
x: (p1.x + p2.x) / 2
y: (p1.y + p2.y) / 2
and the x and y distance to the midpoint from the "p2 you have" point:
d =
x: (p2.x - m.x)
y: (p2.y - m.y)
and then the real p2 is simply that distance away from the "p2 you have":
real2 =
x: p2.x + d.x
y: p2.y + d.y
However, note that this only works for t=0.5: both that projected point on the start--end line and the distance ratios will be (possibly very) different for any other t value and you should use the formula that the Bezier primer talks about.
Also note that what you call "the peak" is in no way guaranteed to be at t=0.5... for example, have a look at this curve:
The point that is marked as belonging to t=0.5 is certainly not where you would say the "peak" of the curve is (in fact, that's closer to t=0.56), so if all you have is three points, you technically always have incomplete information and you're going to have to invent some rule for deciding how to fill in the missing bits. In this case "what t value do I consider my somewhere-on-the-curve point to be?".
Related
I am doing ray tracing with sphere. When we solve quadratic equation and get two roots then which value we need to take? My understanding is that we need to take smallest value. But with that i get wrong results when i put that value in calculating intersection point and further lighting calculations. When I take larger one it gives correct results. I saw some examples on the net and some of them are taking smaller one and others are taking larger. I am really confused which one is correct and why.
Suppose the origin of the ray is O and the direction is R (ideally a unit vector). Then the ray is defined by the parametric equation O + tR. Break this into components Ox + tRx, Oy + tRy and Oz + tRz. Substitute these into the equation for the circle x^2 + y^2 + z^2 = 0. This produces a quadratic equation with the variable t. Find the roots of the equation.
Now, if you have no real roots, the ray doesn't hit the sphere. If you have one real root then you hit the side of the sphere. If you have two real roots, then you hit the sphere twice. You want the closer root (the smaller t) unless t is negative in which case the intersection point is behind you and you don't care. If both roots are negative, then both intersection points are behind the origin of the ray and you can ignore them.
If the sphere is transformed away from the origin and you care about rotation and scaling of the sphere, then the equation of the sphere becomes more complex with xy, yz, xz, x, y and z terms. A general quadric shape is defined as Ax^2 + By^2 + Cy^2 + Dxy + Eyz + Fxz + Gx + Hy + Jz + K = 0. The principle above still applies. Substitute the parametric line equation in, solve for t, take the smallest non-negative root.
Your intersection point is O+tR where t is the smallest non-negative root. From there, I don't know why your lighting calculations would be off.
I have the plane equation describing the points belonging to a plane in 3D and the origin of the normal X, Y, Z. This should be enough to be able to generate something like a 3D arrow. In pcl this is possible via the viewer but I would like to actually store those 3D points inside the cloud. How to generate them then ? A cylinder with a cone on top ?
To generate a line perpendicular to the plane:
You have the plane equation. This gives you the direction of the normal to the plane. If you used PCL to get the plane, this is in ModelCoefficients. See the details here: SampleConsensusModelPerpendicularPlane
The first step is to make a line perpendicular to the normal at the point you mention (X,Y,Z). Let (NORMAL_X,NORMAL_Y,NORMAL_Z) be the normal you got from your plane equation. Something like.
pcl::PointXYZ pnt_on_line;
for(double distfromstart=0.0;distfromstart<LINE_LENGTH;distfromstart+=DISTANCE_INCREMENT){
pnt_on_line.x = X + distfromstart*NORMAL_X;
pnt_on_line.y = Y + distfromstart*NORMAL_Y;
pnt_on_line.z = Z + distfromstart*NORMAL_Z;
my_cloud.points.push_back(pnt_on_line);
}
Now you want to put a hat on your arrow and now pnt_on_line contains the end of the line exactly where you want to put it. To make the cone you could loop over angle and distance along the arrow, calculate a local x and y and z from that and convert them to points in point cloud space: the z part would be converted into your point cloud's frame of reference by multiplying with the normal vector as with above, the x and y would be multiplied into vectors perpendicular to this normal vectorE. To get these, choose an arbitrary unit vector perpendicular to the normal vector (for your x axis) and cross product it with the normal vector to find the y axis.
The second part of this explanation is fairly terse but the first part may be the more important.
Update
So possibly the best way to describe how to do the cone is to start with a cylinder, which is an extension of the line described above. In the case of the line, there is (part of) a one dimensional manifold embedded in 3D space. That is we have one variable that we loop over adding points. The cylinder is a two dimensional object so we have to loop over two dimensions: the angle and the distance. In the case of the line we already have the distance. So the above loop would now look like:
for(double distfromstart=0.0;distfromstart<LINE_LENGTH;distfromstart+=DISTANCE_INCREMENT){
for(double angle=0.0;angle<2*M_PI;angle+=M_PI/8){
//calculate coordinates of point and add to cloud
}
}
Now in order to calculate the coordinates of the new point, well we already have the point on the line, now we just need to add it to a vector to move it away from the line in the appropriate direction of the angle. Let's say the radius of our cylinder will be 0.1, and let's say an orthonormal basis that we have already calculated perpendicular to the normal of the plane (which we will see how to calculate later) is perpendicular_1 and perpendicular_2 (that is, two vectors perpendicular to each other, of length 1, also perpendicular to the vector (NORMAL_X,NORMAL_Y,NORMAL_Z)):
//calculate coordinates of point and add to cloud
pnt_on_cylinder.x = pnt_on_line.x + 0.1 * perpendicular_1.x * 0.1 * cos(angle) + perpendicular_2.x * sin(angle)
pnt_on_cylinder.y = pnt_on_line.y + perpendicular_1.y * 0.1 * cos(angle) + perpendicular_2.y * 0.1 * sin(angle)
pnt_on_cylinder.z = pnt_on_line.z + perpendicular_1.z * 0.1 * cos(angle) + perpendicular_2.z * 0.1 * sin(angle)
my_cloud.points.push_back(pnt_on_cylinder);
Actually, this is a vector summation and if we were to write the operation as vectors it would look like:
pnt_on_line+perpendicular_1*cos(angle)+perpendicular_2*sin(angle)
Now I said I would talk about how to calculate perpendicular_1 and perpendicular_2. Let K be any unit vector that is not parallel to (NORMAL_X,NORMAL_Y,NORMAL_Z) (this can be found by trying e.g. (1,0,0) then (0,1,0)).
Then
perpendicular_1 = K X (NORMAL_X,NORMAL_Y,NORMAL_Z)
perpendicular_2 = perpendicular_1 X (NORMAL_X,NORMAL_Y,NORMAL_Z)
Here X is the vector cross product and the above are vector equations. Note also that the original calculation of pnt_on_line involved a vector dot product and a vector summation (I am just writing this for completeness of the exposition).
If you can manage this then the cone is easy just by changing a couple of things in the double loop: the radius just changes along its length until it is zero at the end of the loop and in the loop distfromstart will not start at 0.
Given a description of an arc which has a startpoint and endpoint (both in Cartesian x,y coordinates), radius and direction (clockwise or counter-clockwise), I need to convert the arc to one with a start-angle, end-angle, center, and radius.
Is there known algorithm or pseudo code that allows me to do this? Also, is there any specific term to describe these kinds of transformations?
You can find a center solving this equation system:
(sx-cx)^2 + (sy-cy)^2=R^2
(ex-cx)^2 + (ey-cy)^2=R^2
where (sx,sy) are coordinates of starting point, (ex,ey) for ending point, unknowns cx, cy for center.
This system has two solutions. Then it is possible to find angles as
StartAngle = ArcTan2(sy-cy, sx-cx)
EndAngle = ArcTan2(ey-cy, ex-cx)
Note that known direction doesn't allow to select one from two possible solutions without additional limitations. For example, start=(0,1), end=(1,0), R=1 and Dir = clockwise give us both Pi/2 arc with center (0,0) and 3*Pi/2 arc with center (1,1)
I'd propose a different approach than MBo to obtain the centers of the two circles, which have the given radius and pass to both start and end point.
If P and Q are start and end point of the arc, the center of each of the two circles lies on the line L which is orthogonal to PQ, the line from P to Q, and which bisects PQ. The distance d from the centers to L is easily obtained by Pythagoras theorem. If e is the length of PQ, then d^2 + (e/2)^2 = r^2. This way you avoid to solve that system of equations you get from MBo's approach.
Note that, in case you have a semicircle, any approach will become numerically unstable because there is only one circle of the given radius with P and Q on it. (I guess I recall the correct term is 'the problem is ill posed' in that case. It happens when P and Q are precisely 2r apart, and to figure out whether this actually true you need to check for equality of two doubles, which is always a bit problematic. If, for some reason, you know you have a semicircle you are better of to just calculate the center of PQ).
I am trying to reconstruct original graphics primitives from Postscript/SVG paths. Thus an original circle is rendered (in SVG markup) as:
<path stroke-width="0.5" d="M159.679 141.309
C159.679 141.793 159.286 142.186 158.801 142.186
C158.318 142.186 157.925 141.793 157.925 141.309
C157.925 140.825 158.318 140.432 158.801 140.432
C159.286 140.432 159.679 140.825 159.679 141.309" />
This is an approximation using 4 Beziers curves to create a circle.In other places circular arcs are approximated by linked Bezier curves.
My question is whether there is an algorithm I can use to recognize this construct and reconstruct the "best" circle. I don't mind small errors - they will be second-order at worst.
UPDATE: Note that I don't know a priori that this is a circle or an arc - it could be anything. And there could be 2, 3 4 or possibly even more points on the curve. So I'd really like a function of the sort:
error = getCircleFromPath(path)
where error will give an early indication of whether this is likely to be a circle.
[I agree that if I know it's a circle it's an easier problem.]
UPDATE: #george goes some way towards answering my problem but I don't think it's the whole story.
After translation to the origin and normalization I appear to have the following four points on the curve:
point [0, 1] with control point at [+-d,1] // horizontal tangent
point [1, 0] with control point at [1,+-d] // vertical tangent
point [0, -1] with control point at [+-d,-1] // horizontal tangent
point [-1, 0] with control point at [-1,+-d] // vertical tangent
This guarantees that the tangent at each point is "parallel" to the path direction at the point. It also guarantees the symmetry (4-fold axis with reflection. But it does not guarantee a circle. For example a large value of d will give a rounded box and a small value a rounded diamond.
My value of d appears to be about 0.57. This might be 1/sqrt(3.) or it might be something else.It is this sort of relationship I am asking for.
#george gives midpoint of arc as;
{p1,(p1 + 3 (p2 + p3) + p4)/8,p4}
so in my example (for 1,0 to 0,1) this would be:
[[1,0]+3[1,d]+3[d,1]+[0,1]] / 8
i.e.
[0.5+3d/8, 3d/8+0.5]
and if d =0.57, this gives 0.71, so maybe d is
(sqrt(0.5)-0.5)*8./3.
This holds for a square diamond, but for circular arcs the formula must be more general and I'd be grateful if anyone has it. For example, I am not familiar with Bezier math, so #george's formula was new to me
enter code here
Without doing all the math for you.. this may help:
there are always 4 control points on a bezier.
Your curve is 4 beziers linked together with points 1-4 , 4-7 , 7-10 , and 10-13 the control points
for each part. Points 1 , 4 , 7 and 10 (&13==1) lie exactly on the curve. To see if you have a nice circle calculate:
center = ( p1+p7 )/2 =( {159.679, 141.309} + {157.925, 141.309} ) / 2
= {158.802, 141.309}
verify you get the same result using points 4+10 -> {158.801, 141.309}
Once you know the center you can sample points along the curve and see if you have a constant distance.
If you only have a single bezier arc with 4 points a useful formula is that the midpoint is at
(p1 + 3 (p2 + p3) + p4)/8. So you can find the circle passing through three points:
{p1,(p1 + 3 (p2 + p3) + p4)/8,p4}
and again sample other points on the curve to decide if you indeed have a near circular arc.
Edit
the bezier formula is this:
x=(1-t)^3 p1 + 3 (1-t)^2 t p2 + 3 (1-t) t^2 p3 + t^3 p4 with parameter 0 < t < 1
so for example at t=1/4 you have
x=( 27 p1 + 27 p2 + 9 p3 + 1 p4 ) / 64
so once you find the center you can readily check a few points and calculate their distance.
I suspect if you only want to detect nearly exact circular arcs then checking two extra points with a tight tolerance will do the job. If you want to detect things that are approximately circular I would compute a bunch of points and use the average error as a criteria.
If all your elements are circle-like then you can just get the dimensions through path.getBBox() and generate a circle from there. In this case I'm considering ellipses, but you can easily translate it to actual circle elements:
var path = document.getElementById("circle_path");
var bbox = path.getBBox();
var rx = bbox.width/2;
var ry = bbox.height/2;
var cx = bbox.x + rx;
var cy = bbox.y + ry;
var ellipse = document.createElementNS(xmlns, "ellipse");
ellipse.setAttribute("fill", "none");
ellipse.setAttribute("stroke", "red");
ellipse.setAttribute("stroke-width", 0.1);
ellipse.setAttribute("cx", cx);
ellipse.setAttribute("cy", cy);
ellipse.setAttribute("rx", rx);
ellipse.setAttribute("ry", ry);
svg.appendChild(ellipse);
You can see a demo here:
http://jsfiddle.net/nwHm6/
The endpoints of the Bézier curves are probably on the circle. If so, it's easy to reconstruct the original circle.
Another possibility is to take the barycenter of the control points as the center of the circle because the control points are probably laid out symmetrically around the center. From the center, you get the radius as the average distance of the four control points closest to the center.
One can define an ellipse as a unit circle centred on (0,0), translated (2 params), scaled (2 params), and rotated (1 param). So on each arc take five points (t=0 ¼ ½ ¾ 1) and solve for these five parameters. Next take the in-between four points (t=⅛ ⅜ ⅝ ⅞), and test whether these lie on the same transformed circle. If yes, whoopee!, this is (part of) a transformed circle.
Immediately before and after might be another arc or arcn. Are these the same ellipse? If yes, and the subtended angles touch, then join together your descriptions of the pieces.
How do I find the closest intersection in 2D between a ray:
x = x0 + t*cos(a), y = y0 + t*sin(a)
and m polylines:
{(x1,y1), (x2,y2), ..., (xn,yn)}
QUICKLY?
I started by looping trough all linesegments and for each linesegment;
{(x1,y1),(x2,y2)} solving:
x1 + u*(x2-x1) = x0 + t*cos(a)
y1 + u*(y2-y1) = y0 + t*sin(a)
by Cramer's rule, and afterward sorting the intersections on distance, but that was slow :-(
BTW: the polylines happens to be monotonically increasing in x.
Coordinate system transformation
I suggest you first transform your setup to something with easier coordinates:
Take your point p = (x, y).
Move it by (-x0, -y0) so that the ray now starts at the center.
Rotate it by -a so that the ray now lies on the x axis.
So far the above operations have cost you four additions and four multiplications per point:
ca = cos(a) # computed only once
sa = sin(a) # likewise
x' = x - x0
y' = y - y0
x'' = x'*ca + y'*sa
y'' = y'*ca - x'*sa
Checking for intersections
Now you know that a segment of the polyline will only intersect the ray if the sign of its y'' value changes, i.e. y1'' * y2'' < 0. You could even postpone the computation of the x'' values until after this check. Furthermore, the segment will only intersect the ray if the intersection of the segment with the x axis occurs for x > 0, which can only happen if either value is greater than zero, i.e. x1'' > 0 or x2'' > 0. If both x'' are greater than zero, then you know there is an intersection.
The following paragraph is kind of optional, don't worry if you don't understand it, there is an alternative noted later on.
If one x'' is positive but the other is negative, then you have to check further. Suppose that the sign of y'' changed from negative to positive, i.e. y1'' < 0 < y2''. The line from p1'' to p2'' will intersect the x axis at x > 0 if and only if the triangle formed by p1'', p2'' and the origin is oriented counter-clockwise. You can determine the orientation of that triangle by examining the sign of the determinant x1''*y2'' - x2''*y1'', it will be positive for a counter-clockwise triangle. If the direction of the sign change is different, the orientation has to be different as well. So to take this together, you can check whether
(x1'' * y2'' - x2'' * y1'') * y2'' > 0
If that is the case, then you have an intersection. Notice that there were no costly divisions involved so far.
Computing intersections
As you want to not only decide whether an intersection exists, but actually find a specific one, you now have to compute that intersection. Let's call it p3. It must satisfy the equations
(x2'' - x3'')/(y2'' - y3'') = (x1'' - x3'')/(y1'' - y3'') and
y3'' = 0
which results in
x3'' = (x1'' * y1'' - x2'' * y2'')/(y1'' - y2'')
Instead of the triangle orientation check from the previous paragraph, you could always compute this x3'' value and discard any results where it turns out to be negative. Less code, but more divisions. Benchmark if in doubt about performance.
To find the point closest to the origin of the ray, you take the result with minimal x3'' value, which you can then transform back into its original position:
x3 = x3''*ca + x0
y3 = x3''*sa + y0
There you are.
Note that all of the above assumed that all numbers were either positive or negative. If you have zeros, it depends on the exact interpretation of what you actually want to compute, how you want to handle these border cases.
To avoid checking intersection with all segments, some space partition is needed, like Quadtree, BSP tree. With space partition it is needed to check ray intersection with space partitions.
In this case, since points are sorted by x-coordinate, it is possible to make space partition with boxes (min x, min y)-(max x, max y) for parts of polyline. Root box is min-max of all points, and it is split in 2 boxes for first and second part of a polyline. Number of segments in parts is same or one box has one more segment. This box splitting is done recursively until only one segment is in a box.
To check ray intersection start with root box and check is it intersected with a ray, if it is than check 2 sub-boxes for an intersection and first test closer sub-box then farther sub-box.
Checking ray-box intersection is checking if ray is crossing axis aligned line between 2 positions. That is done for 4 box boundaries.