I am trying to make a 3D scanner based on turntable. This 3D scanner should create a point cloud model to meause of object length, hight and depth. I am working with realsense d435 RGBD camera. While turntable is rotating, I get the point clouds of object that wants to scan. My question is that how can I join these point clouds that has different rotation angle.
My steps are:
Get the point cloud of object. ( I already got it)
Transform the axes of point cloud to world coordinate system. I mean when I import it to meshlab. It should be on xy axis. I made it to)
Use rotation matrix to rotate the point cloud data for real position. I mean, I get the point cloud data that has 90 degree angle from turntable. When I try the rotate it about z axis, it rotates. But the point clouds has 0 degree angle and 90 degree angle doesnt match.
How can I get over from this problem?
Related
My problem is quite simple yet I struggle to solve it correctly.
I have a camera looking towards the ground and I know all the parameters of the shot. So, using some maths I was able to compute the 4 points defining the field of view of the camera (the coordinates on the ground of each image's corners).
Now, from the coordinates (x, y) of a pixel of the image, I would like to know its real coordinates projected on the ground.
I thought that homography was the way to go, but I read here and there that "homography maps a plane seen from a camera to the same plane seen from another" which is a slightly different problem.
What should I use, please?
Edit: Here is an example.
Given this image:
I know everything about the camera that took the picture (height, angles of view, orientation), so I could calculate the coordinates of the four corners forming its field of view on the ground, for example (in centimeters, relative to the camera position, clockwise from top-left): (-300, 500), (300, 500), (100, 50), (-100, 50).
Knowing that the coordinates on the image of the blade of grass are (1750, 480), how can I know its actual coordinates on the ground?
By "knowing everything" about the camera, do you mean you have the camera FOV, rotation and translation with respect to the ground plane? Then it's trivial, right?
Write the camera matrix K = [[f, 0, w/2],[0, f, h/2],[0, 0, 1]]. Let R and t be respectively the 3x3 rotation matrix and 3x1 translation from camera to ground. A point on the ray going through a given pixel p=[u, v, 1] has camera coordinates r = inv(K) * p. Express it in world coordinates as R * r + t, intersect with the ground plane and you are done.
i'm working on a project where i have a cloud of points in space as input data, my goal is to create a surface.
I started by computing a regression plan for the cloud, then i projected my points on the plane using dot products :
My plane is represented by a point and a normal , i construct the axis of the plane's space using cross products then project each point on these axis.
then i triangulate in 2D (that's the point of the whole operation).
My problem is that my points now are in the plane space and i want to get them back to their inital position (inverse the transformation) to have my surface ON my points.
thank you :)
the best way is to keep the original positions and make the triangulation give you the indices rather than the positions , i hope it will help !
My question is similar to 3D Scene Panning in perspective projection (OpenGL) except I don't know how to compute the direction in which to move the mesh.
I have a program in which various meshes can be selected. Once a mesh is selected I want it to translate when click-dragging the cursor. When the cursor moves up, I want the mesh to move up, and so on for the appropriate direction. In other words, I want the mesh to translate in directions along the plane that is perpendicular to the viewing direction.
I have the Vector2 for the Delta (x,y) in cursor postion, and I have the Vector3 viewDirection of the camera and the center of the mesh. How can I figure out which way to translate the mesh in 3d space with the Delta and viewDirection? Will I need other information in order to to this calculation (such as the up, or eye)?
It doesn't matter if if the scale of the translation is off, I'm just trying to figure out the direction right now.
EDIT: for some reason I had a confusion about getting the up direction. Clearly it can be calculated by applying the camera rotation to the specified perspective up vector.
You'll need an additional vector, upDirection, which is the unit vector pointing "up" from your camera. You can now cross-product viewDirection and upDirection to get rightDirection, the vector pointing "right" from your camera.
You want to map y deltas to motion along upDirection (or -upDirection) and x deltas to motion in rightDirection. These vectors are in world-space.
You may want to scale the translation speed to match the mouse speed. If you are using perspective projection you'll want to scale the translation speed with your model's depth with respect to your camera (The further the object is from your camera, the faster you will need to move it if you want it to match the mouse.)
I'm trying to figure out some calculations using arcs in 3d space but am a bit lost. Lets say that I want to animate an arc in 3d space to connect 2 x,y,z coordinates (both coordinates have a z value of 0, and are just points on a plane). I'm controlling the arc by sending it a starting x,y,z position, a rotation, a velocity, and a gravity value. If I know both the x,y,z coordinates that need to be connected, is there a way to calculate what the necessary rotation, velocity, and gravity values to connect it from the starting x,y,z coordinate to the ending one?
Thanks.
EDIT: Thanks tom10. To clarify, I'm making "arcs" by creating a parabola with particles. I'm trying to figure out how to ( by starting a parabola formed by a series particles with an beginning x,y,z,velocity,rotation,and gravity) determine where it will in end(the last x,y,z coordinates). So if it if these are the two coordinates that need to be connected:
x1=240;
y1=140;
z1=0;
x2=300;
y2=200;
z2=0;
how can the rotation, velocity, and gravity of this parabola be calculated using only these variables start the formation of the parabola:
x1=240;
y1=140;
z1=0;
rotation;
velocity;
gravity;
I am trying to keep the angle a constant value.
This link describes the ballistic trajectory to "hit a target at range x and altitude y when fired from (0,0) and with initial velocity v the required angle(s) of launch θ", which is what you want, right? To get your variables into the right form, set the rotation angle (in the x-y plane) so you're pointing in the right direction, that is atan(y/x), and from then on out, to match the usual terminology for 2D problem, rewrite your z to y, and the horizontal distance to the target (which is sqrt(xx + yy)) as x, and then you can directly use the formula in link.
Do the same as you'd do in 2D. You just have to convert your figures to an affine space by rotating the axis, so one of them becomes zero; then solve and undo the rotation.
It's been a while since my math in university, and now I've come to need it like I never thought i would.
So, this is what I want to achieve:
Having a set of 3D points (geographical points, latitude and longitude, altitude doesn't matter), I want to display them on a screen, considering the direction I want to take into account.
This is going to be used along with a camera and a compass , so when I point the camera to the North, I want to display on my computer the points that the camera should "see". It's a kind of Augmented Reality.
Basically what (i think) i need is a way of transforming the 3D points viewed from above (like viewing the points on google maps) into a set of 3d Points viewed from a side.
The conversion of Latitude and longitude to 3-D cartesian (x,y,z) coordinates can be accomplished with the following (Java) code snippet. Hopefully it's easily converted to your language of choice. lat and lng are initially the latitude and longitude in degrees:
lat*=Math.PI/180.0;
lng*=Math.PI/180.0;
z=Math.sin(-lat);
x=Math.cos(lat)*Math.sin(-lng);
y=Math.cos(lat)*Math.cos(-lng);
The vector (x,y,z) will always lie on a sphere of radius 1 (i.e. the Earth's radius has been scaled to 1).
From there, a 3D perspective projection is required to convert the (x,y,z) into (X,Y) screen coordinates, given a camera position and angle. See, for example, http://en.wikipedia.org/wiki/3D_projection
It really depends on the degree of precision you require. If you're working on a high-precision, close-in view of points anywhere on the globe you will need to take the ellipsoidal shape of the earth into account. This is usually done using an algorithm similar to the one descibed here, on page 38 under 'Conversion between Geographical and Cartesian Coordinates':
http://www.icsm.gov.au/gda/gdatm/gdav2.3.pdf
If you don't need high precision the techniques mentioned above work just fine.
could anyone explain me exactly what these params mean ?
I've tried and the results where very weird so i guess i am missunderstanding some of the params for the perspective projection
* {a}_{x,y,z} - the point in 3D space that is to be projected.
* {c}_{x,y,z} - the location of the camera.
* {\theta}_{x,y,z} - The rotation of the camera. When {c}_{x,y,z}=<0,0,0>, and {\theta}_{x,y,z}=<0,0,0>, the 3D vector <1,2,0> is projected to the 2D vector <1,2>.
* {e}_{x,y,z} - the viewer's position relative to the display surface. [1]
Well, you'll want some 3D vector arithmetic to move your origin, and probably some quaternion-based rotation functions to rotate the vectors to match your direction. There are any number of good tutorials on using quaternions to rotate 3D vectors (since they're used a lot for rendering and such), and the 3D vector stuff is pretty simple if you can remember how vectors are represented.
well, just a pice ov advice, you can plot this points into a 3d space (you can do easily this using openGL).
You have to transforrm the lat/long into another system for example polar or cartesian.
So starting from lat/longyou put the origin of your space into the center of the heart, than you have to transform your data in cartesian coord:
z= R * sin(long)
x= R * cos(long) * sin(lat)
y= R * cos(long) * cos(lat)
R is the radius of the world, you can put it at 1 if you need only to cath the direction between yoour point of view anthe points you need "to see"
than put the Virtual camera in a point of the space you've created, and link data from your real camera (simply a vector) to the data of the virtual one.
The next stemp to gain what you want to do is to try to plot timages for your camera overlapped with your "virtual space", definitevly you should have a real camera that is a control to move the virtual one in a virtual space.