A method for matching point regions in images with radial distortion that, given two frames acquired by a camera with radial distortion, estimates the global image distortion and the local transformations undergone by the image regions between frames, for accurately tracking and aligning these image regions in a sequence of frames, for calibrating the radial distortion using only moving image points, or for estimating the relative change in focal length in cameras with radial distortion and variable zoom using only moving image points, and that comprises the following steps: i. selection of a set of image regions N i in the first frame, with i = 1, 2,...,K and K ≥ 1; ii. selection of a suitable motion model w with vector of parameters p for describing the local deformations that would be undergone by an image region N in the case of the camera being a perspective camera with no lens distortion; iii. use of a 2-dimensional mapping function f for modelling the camera radial distortion such that the relation between distorted image points x and undistorted image points u, both expressed in a coordinate system with origin in the image center O, is given by u = f (x;ξ) with f defined as f x ξ = 1 + ξ x T x − 1 x, where ξ is the image distortion parameter that quantifies the effect of lens radial distortion in pixel units; iv. derivation of the warping model v c, that combines the motion model w for perspective images and the radial distortion model f, and that effectively describes the local deformations that are undergone by the image regions; v. derivation of a cost function that provides the cumulative error ε in aligning the K image regions in the first or current frame T, with the putative corresponding regions in the second or following frame I; vi. joint estimation of both the local motion parameters p i of each image region and the global image distortion parameter ξ using an iterative approach for minimizing the cumulative alignment error ε; vii. update of the position and appearance of the image regions N i using the transformation v c derived in (iv) with the parameters p i and ξ estimated in (vi)); characterized in that the cumulative error ε of v) has the form: ε = ∑ i = 1 K ∑ x ∈ N 1 I v c x q i − T x 2 where x are image point coordinates and q i is q i = p i ξ, with p i being the vector of parameters of the motion model w for the case of the image region N i and ξ being the global image distortion parameter; and in that the warping model v c of iv) is obtained by the formula v c x q = f − 1 u ξ ∘ w u p ∘ g c x ξ where q= ( p ξ) is the vector of the warp parameters, f -1 denotes the inverse of f, and g c is given by g c x ξ = 1 + ξ c T c − 1 x with c being the coordinates of the center of the image region and g c is an approximation of f for carrying the minimization of said step vi) using Inverse Compositional Alignment, ICA. i. selection of a set of image regions N i in the first frame, with i = 1, 2,...,K and K ≥ 1; ii. selection of a suitable motion model w with vector of parameters p for describing the local deformations that would be undergone by an image region N in the case of the camera being a perspective camera with no lens distortion; iii. use of a 2-dimensional mapping function f for modelling the camera radial distortion such that the relation between distorted image points x and undistorted image points u, both expressed in a coordinate system with origin in the image center O, is given by u = f (x;ξ) with f defined as f x ξ = 1 + ξ x T x − 1 x, where ξ is the image distortion parameter that quantifies the effect of lens radial distortion in pixel units; iv. derivation of the warping model v c, that combines the motion model w for perspective images and the radial distortion model f, and that effectively describes the local deformations that are undergone by the image regions; v. derivation of a cost function that provides the cumulative error ε in aligning the K image regions in the first or current frame T, with the putative corresponding regions in the second or following frame I; vi. joint estimation of both the local motion parameters p i of each image region and the global image distortion parameter ξ using an iterative approach for minimizing the cumulative alignment error ε; vii. update of the position and appearance of the image regions N i using the transformation v c derived in (iv) with the parameters p i and ξ estimated in (vi)); characterized in that the cumulative error ε of v) has the form: ε = ∑ i = 1 K ∑ x ∈ N 1 I v c x q i − T x 2 where x are image point coordinates and q i is q i = p i ξ, with p i being the vector of parameters of the motion model w for the case of the image region N i and ξ being the global image distortion parameter; and in that the warping model v c of iv) is obtained by the formula v c x q = f − 1 u ξ ∘ w u p ∘ g c x ξ where q= ( p ξ) is the vector of the warp parameters, f -1 denotes the inverse of f, and g c is given by g c x ξ = 1 + ξ c T c − 1 x