Mostly standard pre-prepared questions. Very little directly enquiring about me as a candidate, and I would guess that several of the interviewers hadn't even looked at my CV. Coding tests included coding on image processing algorithms relevant to the role.
SLAM ; python sorting basics, efficent optimization, OOP basics; morphology, Global co-ordinate estimation from camera coordinate , etc. vanishing points, camera extrensic , camera intrinsics , SURF , point descriptors; fundamental matrix essential matrix; deep learning , machine learning ; bundle algorithms
What are fundamental, essential, and homography matrices and how are they different from each other? What are the components of a camera intrinsics matrix? How do you correct for lens distortion? What are the units of the elements in the camera intrinsics matrix? What happens to the camera intrinsics after you crop an image? How do you convert from 3D world coordinates to 2D mage coordinates?
Cannot disclose the questions asked.
1) Camera Intrinsic 2) Crop a small image from a large image, what's the camera intrinsic for the new smaller image 3) 6D pose estimation for textureless objects.
How do you calibrate a camera? How do you obtain the intrinsic values? Show the math.
Most of the technical interview questions were related to orientations and positions of robots, classical Computer vision like Image formation using perspective projection, a lot matrix operations, Camera calibration, Homography
the camera model; classical computer vision problem like corners and edges detection. Projective transformations
Design a pick-and-place pipeline and calculate the transformation matrix between the camera and the end-effector.
How to project a 3D point to the image plane?
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