This mainly involves reducing the effect of motion due to translation or rotation or any movement in camera. In this, Euclidean Motion Model is used instead of Affine or Homographic transformation, because it is adequate for motion stabilization.
goodGeaturesToTrack
) and (calcOpticalFlowPyrLK
). estimateRigidTranform
). calcOpticalFlowPyrLK()
a) nextPts
- output vector of 2D points (with single-precision floating-point coordinates) containing the calculated new positions of input features in the second image.
b) status
– output status vector (of unsigned chars); each element of the vector is set to 1 if the flow for the corresponding features has been found, otherwise, it is set to 0.
c) err
- outputs vector of errors, if the flow wasn’t found then the error is not defined.
estimateRigidTransform()
a) Computes an optimal affine transformation between two 2D point sets.
python video_stabilization.py