What is camera pose estimation?

What is camera pose estimation?

The specific task of determining the pose of an object in an image (or stereo images, image sequence) is referred to as pose estimation. If also the geometry of the object is known, it means that the projected image of the object on the camera image is a well-known function of the object’s pose.

How many point correspondences do you need to compute the homography matrix?

It is because in the case of fundamental matrix, each correspondence point relates to only one constraint(i.e it maps a point to a line in other image). Hence 8 correspondence points are required. But in the case of homography, each correspondence solves two constraints.

Is there way to compute camera pose from homography?

Given K, an intrinsic camera matrix, a reference image from a camera 1 which pose is known and an image from a camera 2 which pose is unknown, is there a way to compute the pose of camera 2 using the homography matrix found between the two images from matched key-points if I know their 3D coordinates (these points may not be coplanar at all)?

How to computing [ are you T ] from the homography matrix?

Computing [R|T] from the homography matrix is a little more complicated than Jav_Rock’s answer. In OpenCV 3.0, there is a method called cv::decomposeHomographyMat that returns four potential solutions, one of them is correct. However, OpenCV didn’t provide a method to pick out the correct one.

How to compute from the homography matrix in OpenCV?

Given an homography and a correctly scaled intrinsics matrix, the function provides a set of four possible rotations and translations. Computing [R|T] from the homography matrix is a little more complicated than Jav_Rock’s answer.

How to calculate homography using point correspondences?

Before going into how to calculate homography using point correspondences, lets briefly discuss some of the properties of a homography matrix. Homography relates points in first view to points in the second view and since there are no constraints in either views it is a full rank (=3) matrix.