Visual tracking with levy flight grasshopper optimization algorithm

Abstract

Grasshopper optimization algorithm (GOA) is a new metaheuristic optimization algorithm that it simulates behavior of grasshopper swarms in nature. In this paper, a tracking framework called improved levy flight grasshopper optimization algorithm (LGOA) tracker is proposed. The levy flight can increase the diversity of population, prevent premature convergence and enhance the capability of jumping out of local optimal optima, thus improving the tracking accuracy. In addition, GOA has been applied to visual tracking for the first time as far as we know. Finally, compared with other optimization-based trackers, experimental results show that our tracker has obvious advantages.