RANSAC Algorithm

RANSAC, which stands for Random Sample Consensus, is an algorithm used to find a reliable model from a set of data that may contain outliers. Imagine trying to fit a straight line to a scatter of points on a graph where some points are random noise. RANSAC randomly selects subsets of the data to create various line models, then tests how well each model fits the overall data. By iterating this process, it identifies the model that best fits the majority of the points, minimizing the influence of the outliers. This makes it useful in fields like computer vision and robotics.