I am currently working, with Matlab, on a 3D simulator whose aim is to move an object (currently it's just a simple circle) in space (using plot3).
Although it's easy to compute a trajectory without any rotation of my object, I do not manage to rotate my object around its own axis. Indeed, I have computed the 3 well-known rotation matrix but it (of course) rotate my object (represented by a set of points) around the axis of my figure (in the "world" system).
For example, the center of inertia of my object (currently the center of my circle) is I whose coordinates are (Xi,Yi,Zi). Thus, I suppose that I need to define an additional system for my object to be able to rotate my object about these 3 new axis composing such a system...
I would like something like:
[X2,Y2,Z2]=Mat*[X1,Y1,Z1] where [X1,Y1,Z1] is the coordinates of a point of my object before the rotation, [X2,Y2,Z2] the coordinates after the rotation and Mat the matrix I am looking for. Of course, the center of inertia must be unchanged whichever the rotation (yaw and/or pitch or/and roll)
However I have no idea about the way to compute such a matrix. The link below summarizes my wish.
Drawing of my problem
Related
I've got a 3d sphere which I've been able to plot a point on using longitude and latitude thanks to some work of another developer I've found online. I think I understand what its doing.
What I need to do now is rotate my planet so the point is always at the top most point (ie the north pole) but I'm not sure how to do this. I'm probably missing some important fundamentals here so I'm hoping the answer can assist in my future learning.
Here's an image showing what I have - The blue line is a line coming from the longitude and latitude I have plotted and I need to rotate the planet so that line is basically pointing directly upwards.
https://ibb.co/2y24FxS
If anyone is able to advise it'd be very much appreciated.
If I'm not mistaken, Unity uses a coordinate system where the y-axis points up.
If the point on your sphere was in the xy-plane, you'd just have to determine the angle between the radius-vector (starts in the center of the sphere, ends on the point in question) and the y-axis, and than rotate by that amount around the z-axis, so that the radius vector becomes vertical. But your point is at an arbitrary location in 3D space - see the image below. So one way to go about it is to first bring the point to the xy-plane, then continue from there.
Calculate the radius vector, which is just r = x-sphereCenter. Make a copy of it, set y to zero, so that you have (x, 0, z) - which is just the projection of the vector r on the horizontal xz-plane - let's call the copy rXZ.
Determine the signed angle between the x-axis and rXZ (use Vector3.SignedAngle(xAxis, rXZ, yAxis), see docs), and create a rotation matrix M1 that rotates the sphere in the opposite direction around the vertical (negate the angle). This should place your point in the xy-plane.
Now determine the angle between r and the y-axis (Vector3.SignedAngle(r, yAxis, zAxis)), and create a new rotation matrix M2 that rotates by that angle around the zAxis. (I think for this second one, the simpler Vector3.Angle will work as well.)
So, what you want now is to combine the two matrices (by multiplying them) into a single transform (I'm assuming this is a transformation in the local coordinate system of the sphere, where (0, 0, 0) is the sphere's center). If I'm not mistaken, Unity uses column-major matrices, so the multiplication order should be M = M2 * M1 (the rightmost matrix is applied first).
Reorient your globe using M as a local transform, and it should bring your point to the top. You can also create M3 = M1.inverse, and then do M = M3 * M2 * M1, to preserve the original angular offset from the xy-plane.
Check for edge cases, such as r already being vertical (pointing straight up, or straight down).
I am writing a program that captures real time images from a scene by two calibrated cameras (so the internal parameters of the cameras are known to us). Using two view geometry, I can find the essential matrix and use OpenCV or MATLAB to find the relative position and orientation of one camera with respect to another. Having the essential matrix, it is shown in Hartley and Zisserman's Multiple View Geometry that one can reconstruct the scene using triangulation up to scale. Now I want to use a reference length to determine the scale of reconstruction and resolve ambiguity.
I know the height of the front wall and I want to use it for determining the scale of reconstruction to measure other objects and their dimensions or their distance from the center of my first camera. How can it be done in practice?
Thanks in advance.
Edit: To add more information, I have already done linear trianglation (minimizing the algebraic error) but I am not sure if it is any useful because there is still a scale ambiguity that I don't know how to get rid of it. My ultimate goal is to recognize an object (like a Pepsi can) and separate it in a rectangular area (which is going to be written as a separate module by someone else) and then find the distance of each pixel in this rectangular area, i.e. the region of interest, to the camera. Then the distance from the camera to the object will be the minimum of the distances from the camera to the 3D coordinates of the pixels in the region of interest.
Might be a bit late, but at least for someone struggling with the same staff.
As far as I remember it is actually linear problem. You got essential matrix, which gives you rotation matrix and normalized translation vector specifying relative position of cameras. If you followed Hartley and Zissermanm you probably chose one of the cameras as origin of world coordinate system. Meaning all your triangulated points are in normalized distance from this origin. What is important is, that the direction of every triangulated point is correct.
If you have some reference in the scene (lets say height of the wall), then you just have to find this reference (2 points are enough - so opposite ends of the wall) and calculate "normalization coefficient" (sorry for terminology) as
coeff = realWorldDistanceOf2Points / distanceOfTriangulatedPoints
Once you have this coeff, just mulptiply all your triangulated points with it and you got real world points.
Example:
you know that opposite corners of the wall are 5m from each other. you find these corners in both images, triangulate them (lets call triangulated points c1 and c2), calculate their distance in the "normalized" world as ||c1 - c2|| and get the
coeff = 5 / ||c1 - c2||
and you get real 3d world points as triangulatedPoint*coeff.
Maybe easier option is to have both cameras in fixed relative position and calibrate them together by stereoCalibrate openCV/Matlab function (there is actually pretty nice GUI in Matlab for that) - it returns not just intrinsic params, but also extrinsic. But I don't know if this is your case.
I'm working on a Matlab script where I have a bunch of objects (particles) within another bigger object (channel or a tube). I can get the centroids of participles and boundaries of the bigger object (stored in a matrix).
I need to figure out if the particle is in the center or the boundary of the tube. The tube has an irregular shape (think sin like figure). I couldn't find a function that can do that within Image Processing library.
Any help will be appreciated.
Thanks!
You can either use some function that tells you if a point is inside a polygon, like
https://de.mathworks.com/help/matlab/ref/inpolygon.html
Or you fill the boundary polygon with a given value, then add another value to each particle coordinate. Now every point with a value of that sum is inside the large object.
Of course you can also use some boolean logic. Large object and particles are true, background is false. Then AND link both matrices/images to get any particles inside the object.
if the boundary of the tube is a polygon you can calculate it's centroid using the formula from:
https://en.wikipedia.org/wiki/Centroid#Centroid_of_a_polygon
Than iterate over all the particles and calculate the euclidean distance between the particle and the centroid of the tube and if it is in close enough you know the particle is in the center.
I have two moving objects with position and orientation data (Euler Angles, Quaternions) relative to ECI coordinate frame. I would like to calculate AZ/EL from what I'm guessing is the "body frame" of the first object. I have attempted to convert both objects into the body frame through rotation matrices (X-Y-Z and Z-Y-X rotation sequence) and calculate a target vector AZ/EL this way but have not had success. I've also tried to get body frame positions and calculate the body axis/angles and convert back to Eulers (relative to body frame). I'm never sure how the coordinate system axes I'm supposedly creating are aligned along my object.
I have found a couple other questions like this answered with Quaternion solutions so that may be the best path to take, however my Quaternion background is weak at best and I fail to see how the computations given result in a target vector.
Any advice would be much appreciated and I'm happy to share my progress/experiences going forward.
get the current NEH transform matrix for the moving object
you must know position and at least two directions from North,East,Height(Up or Altitude) of the moving object otherwise is your problem unsolvable no matter what. This matrix/frame is called NEH (X=North,Y=East,Z=Height) or sometimes also ENU (X=East,Y=North,Z=Up). Look here transform matrix anatomy and here Earth's NEH construction and change the position and radius to match your moving object.
convert point P0 from GCS (global coordinate system) to NEH
simply: P1=Inverse(NEH)*P0 where P1 is now in NEH LCS (Local coordinate system). Both P0,P1 are in homogenous coordinates { x,y,z,w=1 } to allow multiplications with 4x4 matrix so you can compute azimut and elevation directly from it:
Azimut=atanxy(P1.x,P1.y);
Elevation=atan(P1.z/sqrt((P1.x*P1.x)+(P1.y*P1.y)));
where atanxy is mine atan2 (4 quadrant atan) first is dx then dy. I think atan2 in matlab has it in reverse.
[Notes]
Always visually check all frames (especially NEH). Just draw the 3 axises as lines of some length to validate if the result is correct. It should look like on image, just different color for each axis. You can move to next point only if NEH is OK !!!
Check atan2/atanxy operands order and also check goniometric functions units (rad,deg) to avoid confusions.
I have a 3D matrix of data in matlab, but I want to extract an arbitrarily rotated slice of data from that matrix and store it as a 2D matrix, which I can access. Similar to how the slice() function displays data sliced at any angle, except I would also like to be able to view and modify the data as if it were an array.
I have the coordinates of the pivot-point of the plane as well as the angles of rotation (in x, y and z axis), I have also calculated the equation of the plane in the form:
Ax + By + Cz = D
and can extract a 3D matrix containing only the data that fall on that plane, but I don't know how to then convert that into a simple 2D array.
Another way of doing it would be to somehow rotate the source matrix in the opposite direction of the angle of the plane, so as to line up the plane of data with the XY axis, and simply extract that portion of the matrix, but I do not know if rotating a matrix like that is possible.
I hope this hasn't been answered elsewhere, I've been googling it all day, but none of the problems seem to exactly match mine.
Thanks
You can take a look at the code here. I think the function is similar to what you are trying to solve.
The function extracts an arbitrary plane from a volume given the size of the plane, the center point of the plane, and the plane normal, i.e. [A,B,C]. It also outputs the volumetric index and coordinate of each pixel on the plane.
Aha! May have just solved it myself.
To produce the plane equation I rotate a normal vector of (0,0,1) using rotation matrices and then find D. If I also rotate the following vectors:
(1,0,0) //step in the x direction of our 2D array
and
(0,1,0) //step in the y direction of our 2D array
I'll have the gradients that denote how much my coordinates in x,y,z have to change before I step to the next column in my array, or to the next row.
I'll mock this up ASAP and mark it as the answer if it works
EDIT: Ok slight alteration, when I'm rotating my vectors I should also rotate the point in 3D space that represents the xyz coordinates of x=0,y=0,z=0 (although I'm rotating around the centre of the structure, so it's actually -sizex/2,-sizey/2,-sizez/2, where size is the size of the data, and then I simply add size/2 to each coordinate after the rotations to translate it back to where it should be).
Now that I have the gradient change in 3D as I increase the x coordinate of my 2D array and the gradient change as I increase the y coordinate, I can simply loop through all possible x and y coordinates (the resulting array will be 50x50 for a 50x50x50 array, I'm not sure what it will be for irregular sizes, which I'll need to work out eventually) in my 2D array and calculate the resulting 3D coordinates on my plane in the data. My rotated corner value serves as the starting point. Hooray!
Just got to work out a good test for this encompassing all angles and then I'll approve this as an answer