Computer Vision Interview 20 essential Q&A Updated 2026
calibration

Camera Calibration: 20 Essential Q&A

K, distortion coefficients, and how checkerboard-based calibration recovers pinhole parameters.

~12 min read 20 questions Advanced
K matrixdistortionZhangreprojection
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1. What is camera calibration?
2. Intrinsics
3. Extrinsics
4. Matrix K
5. Radial distortion
6. Tangential distortion
7. Brown–Conrady model
8. Zhang method
9. Checkerboard / Charuco
10. Reprojection error
11. calibrateCamera
12. Stereo calibration
13. Fisheye model
14. Principal point
15. Skew γ
16. World coordinate frame
17. Homography vs full calib
18. AR / robotics use
19. When recalibrate
20. Bundle adjustment link
1 What is camera calibration? ⚡ easy
Answer: Estimating intrinsic (focal length, principal point, distortion) and often extrinsic (pose) parameters so pixel measurements map correctly to 3D rays.
2 What are intrinsics? 📊 medium
Answer: Properties of the camera/lens fixed w.r.t. the sensor—encoded in K and distortion coeffs—independent of where the camera sits in the world.
3 What are extrinsics? 📊 medium
Answer: Rigid transform [R|t] from world (or calibration object) frame to camera frame—changes when the camera moves.
4 What is the intrinsic matrix K? 📊 medium
Answer: 3×3 upper-triangular mapping normalized camera coordinates to pixels: focal lengths f_x,f_y, principal point c_x,c_y, optional skew γ.
5 What is radial distortion? 📊 medium
Answer: Lens bends rays—barrel (outward) or pincushion (inward); modeled as r-dependent scaling of image radius from optical center.
6 What is tangential distortion? 📊 medium
Answer: Lens not perfectly parallel to sensor—modeled with extra parameters (p1,p2) shifting points tangentially; common in OpenCV 5-coeff model.
7 Brown–Conrady model? 🔥 hard
Answer: Classic polynomial radial + tangential distortion used in OpenCV calibrateCamera—may use k1–k3, p1,p2; fisheye uses different high-FOV model.
8 How does Zhang’s method work? 🔥 hard
Answer: Uses multiple views of a planar calibration pattern; each view gives a homography constraining intrinsics; closed-form init then non-linear refinement minimizing reprojection error.
9 Why checkerboards? 📊 medium
Answer: Corner intersections are easy to detect sub-pixel; known 3D layout on plane gives 2D–3D correspondences per image.
10 What is reprojection error? 📊 medium
Answer: Distance between detected image points and projection of 3D model points with estimated parameters—lower is better; report RMS in pixels.
11 OpenCV pipeline? ⚡ easy
Answer: findChessboardCorners → calibrateCamera → get K, distCoeffs; optional stereoCalibrate for two cameras. 
ret, K, dist, rvecs, tvecs = cv2.calibrateCamera(obj_pts, img_pts, image_size, None, None)
12 Stereo calibration? 🔥 hard
Answer: Estimate intrinsics per camera plus relative pose (R,T) between cameras and often rectify so epipolar lines align—needed for triangulation.
13 When use fisheye module? 📊 medium
Answer: Very wide FOV where polynomial model breaks—OpenCV fisheye:: namespace uses different distortion and projection.
14 Principal point? ⚡ easy
Answer: Optical axis intersection with image plane (c_x,c_y)—often near image center but not exactly; important for undistortion and 3D.
15 Skew γ? 🔥 hard
Answer: Non-orthogonal pixel axes—often assumed 0 for modern sensors; included in full K for completeness.
16 World frame choice? 📊 medium
Answer: Usually attach to calibration board plane (Z=0 on pattern)—extrinsics are board-to-camera per capture.
17 Calibrate from homography only? 📊 medium
Answer: Single plane gives partial constraints—need multiple orientations/distances to fix intrinsics uniquely (Zhang’s multi-view idea).
18 Why calibrate for AR? ⚡ easy
Answer: Overlay virtual objects requires accurate projection and undistortion—wrong K causes “swimming” augmentations.
19 When recalibrate? ⚡ easy
Answer: Zoom/focus change, different camera, temperature extremes, or new lens—intrinsics are not universal across devices.
20 Link to bundle adjustment? 🔥 hard
Answer: Joint non-linear refinement of many cameras and 3D points—structure-from-motion and SLAM extend calibration ideas to large scenes.

Calibration Cheat Sheet

Intrinsics
  • K, distortion
Method
  • Zhang + board
  • Min reprojection
Stereo
  • Relative pose
  • Rectification

💡 Pro tip: Intrinsics are camera-specific; extrinsics change per pose.

Full tutorial track

Go deeper with the matching tutorial chapter and code examples.

Calibration Tutorial
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