System and method for camera tracking and pose estimation

A method of tracking a pose of a moving camera, comprising the steps of:

• providing a set of 3-dimensional model points that represent an edge in a digitized reference image;
• receiving a digitized observed image from a camera, said image comprising a plurality of intensities corresponding to a domain of points on a 2-dimensional grid;
• providing an initial pose estimation of a camera for a first image in a sequence of images;
• detecting a set of data points in a next image of said sequence of images, said set of data points including an edge corresponding to the edge in said model point set;
• defining a kernel density estimator for a probability density function that represents the probability that a point in said data set belongs to said edge;
• warping and resampling the set of model points to correspond to the set of data points according to the initial pose estimation;
• and
• maximizing a kernel-density correlation function of the warped and resampled model point set, wherein said maximized function provides an estimate of the camera pose of said next image in said sequence of images.

A program storage device readable by a computer, tangibly embodying a program of instructions executable by the computer to perform the method steps for tracking a pose of a moving camera, said method comprising the steps of:

• receiving a first received digitized image from a camera, said image comprising a plurality of intensities corresponding to a domain of points on a 2-dimensional grid, and including one or more landmarks for tracking;
• receiving a sequence of digitized images from said camera, each image comprising a plurality of intensities corresponding to a domain of points on a 2-dimensional grid;
• recording, for each of said sequence of digitized images, the pose and 2D correspondences of each of said landmarks;
• reconstructing a location and appearance of a 2-dimensional texture patch from the 2D correspondences of the landmarks of said sequence of digitized images by triangulation and optimization;
• computing back-projection errors by comparing said reconstructed texture patch with said first received image;
• and
• reconstructing said location and appearance of said 2-dimensional texture patch from the 2D correspondences of the landmarks of said sequence of digitized images by triangulation and optimization after eliminating those landmarks with large back-projection errors.