The present real-time tracking algorithm can perform well in term of translation tracking but can seldom do so in rotation tracking. A rotation tracking algorithm was proposed

which utilized the gray gradient direction distribution of the target region as the feature and constructed a similarity function that can be optimized by Mean Shift method. Therefore the rotation tracking was transformed into an optimization problem. Due to the fast convergence of the Mean Shift

this algorithm can be run in real-time. Combining the rotation tracking with the translation tracking algorithm proposed by Meer

a whole algorithm was obtained by alternate iteration

which can track both translation and rotation of the targets.