Question

In „Multiple View Geometry in Computer Vision” R.Hartley,A.Zisserman in chapter 11 - about computation Fundamental Matrix one can read:

11.7.3 The calibrated case

In the case of calibrated cameras normalized image coordinates may be used, and the essential matrix E computed instead of the fundamental matrix

Does it mean – if I have proper Intrinsic Cameras matrices (does it mean calibrated in this case?) I can calculate Essential Matrix directly (using 8 points algorithm) omitting calculating Fundamental Matrix?

And I can get matrices R and T from calculated Essential Matrix to reconstruction 3D model?

Regards,

Artik

Was it helpful?

Solution

Short answer, yes. See also longer explanation on Wikipedia.

OTHER TIPS

From your correspondences, using the 8point Alg you obtain the Fundamental Matrix F. From the relation E=K'^T F K, assuming that you know both K' and K (in case that both the images were taken by the same camera, you have K'=K), you can compute E. From E you get 4 possible camera couple (P_0,P_0') (P_1,P_1')....(P_3,P_3'). Only one of this couple satisfy the positive depth constraint (i.e. the 3D points lie in front of both the cameras). That couple will be your cameras. Hope this help!

So, In general, a calibrated camera in visual odometry refers to a camera for which the intrinsic matrix is known.

In the case of a stereo visual odometry system, I typically take it to mean that the intrinsic matrix is known for both cameras, however, some of my co-works mean it to mean that the Rotation and Translation between the two cameras are known.

In Practice, there is hardly any distinction between the two as you can estimate the intrinsic matrix of a camera using various functions in MatLab or OpenCV, and given the instinct matrix, you can determine the rotation and translation between the two cameras.

Furthermore, the derivation of the fundamental matrix relies upon the Essential matrix and the intrinsic matrix of two cameras (the intrinsic matrix can be the same in the case of monocular visual odometry). This means that it is often the case that the essential matrix is estimated and the fundamental matrix is not.

For an explanation on getting the rotation and translation from the essential matrix, I recommend first watching a youtube video on Single Value Decomposition (SVD) and then reading: https://www.researchgate.net/publication/220556161_Visual_Odometry_Tutorial.

Good Luck with Your Studies Young Scholar.

Licensed under: CC-BY-SA with attribution
Not affiliated with StackOverflow
scroll top