Ellipse motion estimation using parametric snakes

Abstract

In this paper we propose a multiscale parametric snake model for ellipse motion estimation across a sequence of images. We use a robust ellipse parameterization based on the geometry of the intersection of a cylinder and a plane. The ellipse parameters are optimized in each frame by searching for local minima of the snake model energy including temporal coherence in the ellipse motion. One advantage of this method is that it just considers the convolution of the image with a Gaussian kernel and its gradient, and no edge detection is required. A detailed study about the numerical evaluation of the snake energy on ellipses is presented. We propose a Newton–Raphson-type algorithm to estimate a local minimum of the energy. We present some experimental results on synthetic data, real video sequences and 3D medical images.