photogrammetry

Given a picture taken by a simple digital that contains an image of a rectangle of known dimensions. How can I - to some degree of accuracy - determine the parameters of this camera? I am mostly interested in Pan-, Tilt- and Swing angles. Optionally distance to the rectangle would be nice. I acknowledge the fact that the focal length and resolution of the camera should be known, but it can be assumed that they are available (for example through exif metadata). Are there any simple algorithms for this problems? What you are looking for are camera calibration algorithms. A commonly used one is

So what I need to do is measuring a foot length from an image taken by an ordinary user. That image will contain a foot with a black sock wearing, a coin (or other known size object), and a white paper (eg A4) where the other two objects will be upon. What I already have? -I already worked with opencv but just simple projects; -I already started to read some articles about Camera Calibration ( "Learn OpenCv" ) but still don't know if I have to go so far. What I am needing now is some orientation because I still don't understand if I'm following right way to solve this problem. I have some

I'd like to calculate size of object in a photo which includes both a target object and a reference one . I think what I'd like to do is what this software achieves (I don't know how precise this software is) https://itunes.apple.com/us/app/photo-meter-picture-measuring/id579961082?mt=8 I've already found, in general, it's called photogrammetry and seems active research field. How would you find the height of objects given an image? https://physics.stackexchange.com/questions/151121/can-i-calculate-the-size-of-a-real-object-by-just-looking-at-the-picture-taken-b But, I can not find what is

I am working on a project using the Orb feature detector in OpenCV 2.3.1 . I am finding matches between 8 different images, 6 of which are very similar (20 cm difference in camera position, along a linear slider so there is no scale or rotational variance), and then 2 images taken from about a 45 degree angle from either side. My code is finding plenty of accurate matches between the very similar images, but few to none for the images taken from a more different perspective. I've included what I think are the pertinent parts of my code, please let me know if you need more information. // set

I have a video file recorded from the front of a moving vehicle. I am going to use OpenCV for object detection and recognition but I'm stuck on one aspect. How can I determine the distance from a recognized object. I can know my current speed and real-world GPS position but that is all. I can't make any assumptions about the object I'm tracking. I am planning to use this to track and follow objects without colliding with them. Ideally I would like to use this data to derive the object's real-world position, which I could do if I could determine the distance from the camera to the object. When

I have 4 2D points in screen-space, and I need to reverse-project them back into 3D space. I know that each of the 4 points is a corner of a 3D-rotated rigid rectangle, and I know the size of the rectangle. How can I get 3D coordinates from this? I am not using any particular API, and I do not have an existing projection matrix. I'm just looking for basic math to do this. Of course there isn't enough data to convert a single 2D point to 3D with no other reference, but I imagine that if you have 4 points, you know that they're all at right-angles to each other on the same plane, and you know