  Multiple objects tracking (MOT) is a difficult task, as it usually requires
special hardware and higher computation complexity. In this work, we present a
new framework of MOT by using of equilibrium optimizer (EO) algorithm and
reducing the resolution of the bounding boxes of the objects to solve such
problems in the detection free framework. First, in the first frame the target
objects are initialized and its size is computed, then its resolution is
reduced if it is higher than a threshold, and then modeled by their kernel
color histogram to establish a feature model. The Bhattacharya distances
between the histogram of object models and other candidates are used as the
fitness function to be optimized. Multiple agents are generated by EO,
according to the number of the target objects to be tracked. EO algorithm is
used because of its efficiency and lower computation cost compared to other
algorithms in global optimization. Experimental results confirm that EO
multi-object tracker achieves satisfying tracking results then other trackers.
