Explain the pinhole camera model and intrinsic matrix K
Tests projective geometry and mapping sensor properties to K. Good answers derive perspective projection via similar triangles, list fx, fy, cx, cy, skew, and explain pixel scaling. Red flag: mixing intrinsics with extrinsics or saying K includes distortion.
Tests projective geometry intuition and whether you can map physical camera properties into K. A strong answer derives perspective projection via similar triangles, then lists K's parameters: focal lengths fx and fy in pixel units, principal point cx and cy, and optional skew. It notes fx and fy fold in focal length and pixel density, while cx and cy encode sensor offset from the optical axis. Red flag: mixing intrinsics with extrinsics, omitting the physical meaning of focal lengths, or claiming K includes radial distortion.
Read the original → Wikipedia: Pinhole camera model
- #computer vision
- #pinhole camera
- #intrinsic matrix
- #projective geometry
- #camera calibration
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