Multiple Object Tracking Based On Firefly Algorithm And FSIM

Multiple object tracking is an active area of research in computer vision. Using different strategies such as optimization solutions, estimators, filters and other solutions that can be adapted to the tracking problem, is aim for many researchers to achieve more acceptable results. This paper introduces new approach to improve accuracy of multiple object tracking based on optimization solution using firefly algorithm. Firefly is a new meta heuristic optimization algorithm. It has some characteristics like PSO algorithm with better performance in optimization problems. In this approach, the similarity between the primary objects window and the secondary objects window in each frame selected as the objective function. Then, we use FSIM algorithm to calculate the similarity between two windows. At the end, problem of locating these windows in each frame is solving by Firefly optimization algorithm. Experimental results approve that the proposed method improves greatly the tracking accuracy during different challenges, like occlusion, low quality, complex background and Unanticipated movements.

Keywords:

multiple object tracking , optimization , firefly algorithm , FSIM algorithm