Detecting the Face from camera may be affected by some uncontrolled illumination. Due to this effect low resolution faces may be acquired. Although the face tracking in the video is ineffective due to the low resolution face which contains limited information and there may be illumination on the small region of the face. To overcome this problem we use gradient logarithm field (GLF) because it is effective in tracking the low resolution faces. In many video surveillance applications the faces acquired by cameras are ineffective. Due to the low resolution faces and uncontrolled illumination. This problem may be overcomed by using gradient logarithm field (GLF).GLF is the global feature model and it is effective in tracking low resolution videos. GLF based tracker works well on illumination changes and outperforms many state-of the-art tracking algorithms. In the performance we plot the graph for error of tracking results. We proposed and evaluated a GLF tracker to address the problem of tracking a low resolution face subject to illumination changes. The GLF feature mainly depends on the intrinsic characteristics of a face and is only marginally affected by the lighting source. In addition, the GLF feature is a global feature and does not depend on a specific face model, and thus is effective in tracking low-resolution faces. Experimental results show that the proposed GLF-based tracker works well under significant illumination changes and outperforms many state-of the-art tracking algorithms.