Visual tracking using meta-heuristic optimal algorithm

Visual tracking has emerged as a crucial task in several applications e.g. robotics surveillance vision-based control and human computer interfaces. However visual tracking is still a challenging task. In the monograph visual tracking is interpreted as an optimization problem. Two meta-heuristic optimal algorithms namely bat algorithm and harmony search are applied to solve tracking problems. The monograph presents a new way to solve visual tracking problem and expands the applications of meta-heuristic optimal algorithm.