Ellipse Fitting

Ellipse fitting involves accurately determining the parameters of an ellipse (or higher-dimensional ellipsoid) from a set of data points, aiming for robust and efficient algorithms that handle noise and outliers. Current research emphasizes developing novel algorithms, including Bayesian approaches and those incorporating deep learning architectures like transformers, to improve accuracy and speed, particularly in challenging scenarios with incomplete or noisy data. These advancements find applications in diverse fields, such as eye tracking in extended reality, food image processing, 3D shape reconstruction, and material characterization through optical ellipsometry, highlighting the broad utility of robust ellipse fitting techniques.