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Multiple objects tracking (MOT) is a difficult task, as it usually requiresspecial hardware and higher computation complexity. In this work, we present anew framework of MOT by using of equilibrium optimizer (EO) algorithm andreducing the resolution of the bounding boxes of the objects to solve suchproblems in the detection free framework. First, in the first frame the targetobjects are initialized and its size is computed, then its resolution isreduced if it is higher than a threshold, and then modeled by their kernelcolor histogram to establish a feature model. The Bhattacharya distancesbetween the histogram of object models and other candidates are used as thefitness function to be optimized. Multiple agents are generated by EO,according to the number of the target objects to be tracked. EO algorithm isused because of its efficiency and lower computation cost compared to otheralgorithms in global optimization. Experimental results confirm that EOmulti-object tracker achieves satisfying tracking results then other trackers.

Real Time Detection Free Tracking of Multiple Objects Via Equilibrium Optimizer