Focusing on the issue that the traditional kernelized correlation filter (KCF) has poor performance in handing heavy occlusion and illumination variations, a long-term KCF tracking algorithm is proposed combined with fast corner detection and bidirectional optical flow method. First, the KCF tracker is used to extract the multi-channel features of the histogram of gradient, color attributes, and gray features at the target location. The output response map is calculated and the peak sidelobe ratio (PSR) of the tracked target is obtained. The PSR and the empirical threshold determine whether the target is occluded by comparison. When the target is occluded, the bidirectional optical flow method is used to redetect the target position of the next frame based on the corner points detected by the fast corner detection, and a new template updating strategy is adopted to deal with the heavy occlusion. Compared with other algorithms, the proposed algorithm is effective and robust to the processing of occlusion and illumination variations.