Authors : Hathiram Nenavath and Ravi Kumar Jatoth
Abstract: The new metaheuristic algorithm used for optimization is Binary Bat Algorithm (BBA) which is motivated by echolocation features of bats whose pulse rates vary in loudness and emission. BBA has been recognized as one of the powerful algorithms to obtain a solution for a diversity of global optimization problems. In this research to solve the problem of tracking a novel binary bat algorithm based tracking architecture is proposed. The proposed BBA based tracking architecture is used to measure object tracking error, absolute error, tracking detection rate, root mean square error and time cost experimentally as parameters for BBA. The tracking results depicts that the BBA-based tracker can robustly track a random target in different challenging situations. To reveal the capability of tracker proposed in this research, a comparison of BBA based tracker and other trackers, viz., Alpha-Beta (α-β) filter, Linear Kalman Filter (LKF), Extended Kalman Filter (EKF) and Bat Algorithm (BA) is presented.
Hathiram Nenavath and Ravi Kumar Jatoth, 2018. A Novel Object Tracking Method Using Binary Bat Algorithm. Journal of Engineering and Applied Sciences, 13: 3817-3825.