In this paper, a method for unknown object tracking in output images from 360-degree cameras called Modified Training-Learning-Detection (MTLD) is presented. The proposed method is based on the recently introduced Training-Learning-Detection (TLD) scheme in the literature. The flaws of the TLD approach have been detected and significant modifications are proposed to enhance and to elaborate the scheme. Unlike TLD, MTLD is capable of detecting the unknown objects of interest in 360-degree images. According to the experimental results, the proposed method significantly outperforms the TLD method in terms of detection rate and implementation cost.