Tracking shots have posed a significant challenge for salient region detection due to the presence of highly competing background motion. In this paper, we propose a computationally efficient technique to detect salient objects in a tracking shot. We first separate the tracked foreground pixels from the background by accounting for the variability of the pixels in a set of frames. The focus of the tracked foreground pixels is utilized as a measure of saliency of objects in the scene. We evaluate the performance of this method by comparing the salient region detection with ground truth data of the location of the salient object that are manually generated. The results of the evaluation show that the proposed method is able to achieve superior salient object detection performance with very low computational load.