Voting the outliers away
A point set with a hidden true line and adjustable outliers. One button draws a single random candidate and counts its inliers; the other runs the adaptive loop until the N(w) formula says 99% confidence has been reached.
Try this
Click on the canvas to add outliers and watch the required iteration count climb — slowly at first, then not slowly at all.
Where this lab comes from
RANSAC: How Vision Algorithms Vote Away OutliersRANSAC separates data into inliers and outliers by fitting models to random minimal samples and keeping the one with the largest consensus. Walked end to end on two vision problems: a walking-speed estimate that three false detections drag from 2.00 m/s to 0.78, and a basketball shot called from a 3-point parabola fit. Plus the one-line formula for how many samples you need, a hands-on lab, and real inlier ratios measured on the temple dataset.
More in cameras and geometry
- Focus, aperture and depth of field — Move the subject and watch the focus plane and the blur follow.
- Four ways a fisheye maps angle to radius — Plot r(θ) for the classical designs against a fitted curve.
- The scene, and what the camera sees — Orbit a 3-D scene on the left; the pinhole view updates on the right.