Feature Tracking from an Image Sequence Using Geometric Invariants

In this paper two new feature tracking algorithms are proposed. In the first algorithm, a perspective camera model is used. Making use of the projective inuari-ant of Barrett, and assuming the image feature points corresponding to 8 general points in space are tracked by a conventional method in the image sequence, the other feature points in the sequence can be tracked us-ing a Hough technique. Correspondence between two reference images as required by the original Barrett’s invariant is not necessary. In the second algorithm, an afine camera model is assumed and the image fea-ture points corresponding to 4 non-coplanar points in space are assumed tracked in the image sequence us-ing a conventional method. These image points form the basis of afine coordinates in each image. After the correspondence of a fifth point is established be-tween the first two images, the afine coordinates of all image points in the first images existence can be computed. As far as we know, this is the only algo-rithm which can transfer a point knowing only a single image. Experiments showed that both algorithms gave highly accurate tracking results