High Accuracy Ellipse-Specific Fitting

We propose a new method that always fits an ellipse to a point sequence extracted from images. The currently known best ellipse fitting method is hyper-renormalization of Kanatani et al., but it may return a hyperbola when the noise in the data is very large. Our proposed method returns an ellipse close to the point sequence by random sampling of data points. Doing simulation, we show that our method has higher accuracy than the method of Fitzgibbon et al. and the method of Szpak et al., the two methods so far proposed to always return an ellipse.