I am a beginner when it comes to computer vision so I apologize in advance. Basically, the idea I am trying to code is that given two cameras that can simulate a multiple baseline stereo system; I am trying to estimate the pose of one camera given the other.
Looking at the same scene, I would incorporate some noise in the pose of the second camera, and given the clean image from camera 1, and slightly distorted/skewed image from camera 2, I would like to estimate the pose of camera 2 from this data as well as the known baseline between the cameras. I have been reading up about homography matrices and related implementation in opencv, but I am just trying to get some suggestions about possible approaches. Most of the applications of the homography matrix that I have seen talk about stitching or overlaying images, but here I am looking for a six degrees of freedom attitude of the camera from that.
It'd be great if someone can shed some light on these questions too: Can an approach used for this be extended to more than two cameras? And is it also possible for both the cameras to have some 'noise' in their pose, and yet recover the 6dof attitude at every instant?
Let's clear up your question first. I guess You are looking for the pose of the camera relative to another camera location. This is described by Homography only for pure camera rotations. For General motion that includes translation this is described by rotation and translation matrices. If the fields of view of the cameras overlap the task can be solved with structure from motion which still estimates only 5 dof. This means that translation is estimated up to scale. If there is a chessboard with known dimensions in the cameras' field of view you can easily solve for 6dof by running a PnP algorithm. Of course, cameras should be calibrated first. Finally, in 2008 Marc Pollefeys came up with an idea how to estimate 6 dof from two moving cameras with non-overlapping fields of view without using any chess boards. To give you more detail please tell a bit for the intended appljcation you are looking for.