1. A computer implemented method of tracking a pose of a moving camera, the method performed by the computer 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; 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 searching for a best match of each landmark correspondence in said reconstructed texture patch, wherein a search range is determined by a maximum back-projection error, wherein said best match is found by minimizing a sum of square differences d ⁡ ( I norm ) 2 = ∑ i = 0 , j = 0 i < n p , j < n p ⁢ ( I c norm ⁡ ( i c , j c ) - I 0 norm ⁡ ( i , j ) ) 2 , wherein n p , is a size of said texture patch for each landmark, i c and j c are feature point coordinates, I norm is the normalized intensity of a point defined by I norm = I - I avg I max - I min , wherein I is a intensity before normalization, and I avg , I max and I min , are the average, maximum, and minimum intensity values of the texture patch, respectively; and determining a likelihood score S l,k for each feature point k of landmark l from S l , k = w λ ⁡ ( λ ⁡ ( u c , v c ) - λ 0 ) + w l ⁢ d ⁡ ( I norm ) 2 ⁢ / ⁢ n pix , wherein n pix is the number of pixels in the texture patch of landmark l, λ(u c , v c ) and λ 0 are the smallest eigenvalues of the current candidate pixel (u c ,v c ) and the original pixel, respectively, and w λ and w I are predetermined weighting factors.