Joint segmentation and B-spline object contour modelling for object tracking and motion compensation in image sequences

One problem in tracking an object through video frames and estimating the associated motion parameters is that the object of interest may undergo various affine transformations and a small deformation. This paper presents a multi-stage algorithm for tracking moving objects using joint segmentation and B-spline contour modelling and motion parameters estimation. The segmentation algorithm uses merging thresholds which are based on the local image property. A fast gradient-based B-spline contour matching algorithm and a robust knot re-assignment method are proposed for tracking moving objects through image frames and estimating their motion parameters. The application of the scheme on images of hand and tool movements, and an image sequence containing a screwdriver with affine transformations shows that the estimated parameters are in very close agreement with the actual parameters