Global translation preferred active contour is much more suitable for object tracking. The prior information of active contour with global translation preference can be interpreted as the velocity field along the evolving contour with equivalency preference. According to this

a simple gradient flow which preferes global translation is acquired by defining a new inner product on the set of perturbations of a curve. The new inner product is obtained by adding the variance of the perturbation of a curve to the inner product relative to the 〖WTHX〗H〖WTBZ〗0 active contour. The active contour relative to the new inner product is called variance active contour. In contrast to 〖WTHX〗H〖WTBZ〗1 active contour generated by convolution of 〖WTHX〗H〖WTBZ〗0 active contour and certain kernel functional

variance active contour needs no convolution and is a weighting sum of 〖WTHX〗H〖WTBZ〗0 active contour and corresponding average gradient flow. Thus

variance active contour can be implemented much faster and easier than 〖WTHX〗H〖WTBZ〗1 active contour. We also compared 〖WTHX〗H〖WTBZ〗0

〖WTHX〗H〖WTBZ〗1 and variance active contours in space and frequency domains.