This paper presents an efficient combination of two well-known tracking algorithms, Tracking-Learning-Detection (TLD) and Compressive Tracking (CT) to devise an algorithm which takes advantages of both and outperforms them on their short-ends by virtue of other. TLD fails in cases including full out-of-plane rotation, fast motion and articulated object tracking. While CT fails in resuming tracking once the object leaves the frame and comes back. We propose a combining algorithm mentioned as Algorithm 1, which robustly handles all the tracking challenges. Different thresholds are set which can be varied to weigh each component as required. The proposed algorithm is tested on different test sequences involving challenging tracking scenarios such as fast motion and their success rates are calculated in Table I. The proposed algorithm works favourably against both algorithms in terms of robustness and success rate. © 2015 IEEE.