Motion estimation in image sequences using the deformation of apparent contours

The problem of determining the camera motion from apparent contours or silhouettes of a priori unknown curved 3D surfaces is considered. In a sequence of images, it is shown how to use the generalized epipolar constraint on apparent contours. One such constraint is obtained for each epipolar tangency point in each image pair. An accurate algorithm for computing the motion is presented based on a maximum likelihood estimate. It is shown how to generate initial estimates on the camera motion using only the tracked contours. It is also shown that in theory the motion can be calculated from the deformation of a single contour. The algorithm has been tested on several real image sequences, for both Euclidean and projective reconstruction. The resulting motion estimate is compared to motion estimates calculated independently using standard feature-based methods. The motion estimate is also used to classify the silhouettes as curves or apparent contours. The statistical evaluation shows that the technique gives accurate and stable results.