How can I calculate the distance of an object of known size (e.g. aruco marker of 0.14m printed on paper) from camera. I know the camera matrix (camMatx) and my fx,fy ~= 600px assuming no distortion. From this data I am able to calculate the pose of the aruco marker and have obtained [R|t]. Now the task is to get the distance of the aruco marker from the camera. I also know the height of the camera from ground plane (15m).
How should I go about solving this problem. Any help would be appreciated. Also please note I have also seen approach of similar triangles, but that would work on knowing the distance of the object, which doesnt apply in my case as I have to calculate the distance.
N.B: I dont know the camera sensor height. But I know how high the camera is located above ground.
I know the dimensions of the area in which my object is moving (70m x 45m). In the end I would like to plot the coordinate of the moving object on a 2D map drawn to the scale.
Related
After to calibrated a camera using Jean- Yves Bouget's Camera Calibration Toolbox and checkerboard-patterns printed on cardboard, I´ve obtained extrinsic and intrinsic parameters, I can use the informations to find camera coordinates:
Pc = R * Pw + T
After that, how to obtain the world coordinates of an image using the Pc and calibration parametesr?
thanks in advance.
EDIT
The goal is to use the calibrated camera parameters to measure planar objects with a calibrated Camera). To perform this task i dont know to use the camera parameters. in other words i have to convert the pixels coordinates of the image to world coordinates using the calibrated parameters. I already have the parameters and the new image. How can i do this convertion?
thanks in advance.
I was thinking about problem, and came to the result:
You can't find the object size. The problem is by a single shot, when you have no idea how far the Object is from your camera you can't say something about the size of the object. The calibration just say how far is the image plane from the camera (focal length) and the open angles of the lense. When the focal length changes the calbriation changes too.
But there are some possibiltys:
How to get the real life size of an object from an image, when not knowing the distance between object and the camera?
So how I understand you can approximate the size of the objects.
Your problem can be solved if (and only if) you can express the plane of your object in calibrated camera coordinates.
The calibration procedure outputs, along with the camera intrinsic parameters K, a coordinate transform matrix for every calibration image Qwc_i = [Rwc_i |Twc_i] matrix, that expresses the location and pose of a particular scene coordinate frame in the camera coordinates at that calibration image. IIRC, in Jean-Yves toolbox this is the frame attached to the top-left corner of the calibration checkerboard.
So, if your planar object is on the same plane as the checkerboard in one of the calibration images, all you have to do in order to find its location in space is intersect the checkerboard plane with camera rays cast from the camera center (0,0,0) to the pixels into which the object is imaged.
If your object is NOT in one of those planes, all you can do is infer the object's own plane from additional information, if available, e.g. from a feature of known size and shape.
A quick question, I'm using the Circle Hough Transform to detect balls in an image. Since the algorithm is computationally expensive, I've been wondering if it is possible to calculate the radius of the ball in pixels using camera calibration data. I've read the following question (see below) and figured that if I can find the distance between the camera and the ball, I could calculate the radius somehow, is this possible?
Finding distance from camera to object of known size
Many thanks!
We are currently using opencv to track a planar rectangular target. While directly straight(no pitch), this works perfectly using findContours with solvePnp and returns a very accurate location of the target.
The problem is, is that obviously we get the different results once we increase the pitch. We know the pitch of the camera at all time.
How would I "cancel out" the pitch of the camera, and obtain coordinates as if the camera was facing straight ahead?
In the general case you can use an affine transform to map the quadrilateral seen by the camera back to the original rectangle. In your case the quadrilateral seen by the camera may be a good approximation of a parallelogram since only one angle is changing, but in real-world applications you can generally assume that the camera can have non-zero values for each of the three rotations (e.g. in pitch, yaw, and roll).
http://opencv.itseez.com/doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.html
The transform allows you to calculate the matching coordinates (x,y) within the rectangle's plane given coordinates (x', y') in the image of the rectangle.
I am trying to write a program using opencv to calculate the distance from a webcam to a one inch white sphere. I feel like this should be pretty easy, but for whatever reason I'm drawing a blank. Thanks for the help ahead of time.
You can use triangle similarity to calibrate the camera angle and find the distance.
You know your ball's size: D units (e.g. cm). Place it at a known distance Z, say 1 meter = 100cm, in front of the camera and measure its apparent width in pixels. Call this width d.
The focal length of the camera f (which is slightly different from camera to camera) is then f=d*Z/D.
When you see this ball again with this camera, and its apparent width is d' pixels, then by triangle similarity, you know that f/d'=Z'/D and thus: Z'=D*f/d' where Z' is the ball's current distance from the camera.
To my mind you will need a camera model = a calibration model if you want to measure distance or other things (int the real-world).
The pinhole camera model is simple, linear and gives good results (but won't correct distortions, (whether they are radial or tangential).
If you don't use that, then you'll be able to compute disparity-depth map, (for instance if you use stereo vision) but it is relative and doesn't give you an absolute measurement, only what is behind and what is in front of another object....
Therefore, i think the answer is : you will need to calibrate it somehow, maybe you could ask the user to approach the sphere to the camera till all the image plane is perfectly filled with the ball, and with a prior known of the ball measurement, you'll be able to then compute the distance....
Julien,
I have a problem that involves a UAV flying with a camera mounted below it. Following information is provided:
GPS Location of the UAV in Lat/Long
GPS Height of the UAV in meters
Attitude of the UAV i.e. roll, pitch, and yaw in degrees
Field of View (FOV) of the camera in degrees
Elevation of the camera w.r.t UAV in degrees
Azimuth of camera w.r.t UAV in degrees
I have some some images taken from that camera during a flight and my task is to compute the locations (in Lat/Long) of 4 corners points and the center points of the image so that the image can be placed on the map at proper location.
I found a document while searching the internet that can be downloaded at the following link:
http://www.siaa.asn.au/get/2411853249.pdf
My maths background is very weak so I am not able to translate the document into a working solution.
Can somebody provide me a solution to my problem in the form of a simple algorithm or preferable in the form of code of some programming language?
Thanks.
As I see, it does not related to image-processing, because you need to determine coordinates of center of image (you even do not need FOV). You have to find intersection of camera principal ray and earth surface (if I've understood your task well). This is nothing more then basic matrix math.
See wiki:Transformation.