The spatial regularization correlation filtering tracking algorithm based on deformable diversity similarity is proposed. The spatial regularization weight and the sub-grid detection method are introduced on the basis of the kernelized correlation filtering (KCF) tracking algorithm. The target re-detection module is constructed with deformable diversity similarity matching algorithm, the nearest neighbor search problem in the matching algorithm is solved via the principal component analysis (PCA) algorithm and the k-direction tree coherence approximate nearest neighbor (TreeCANN) algorithm. Through the adaptive template updating strategy, the problem of false updating of the template under occlusion is solved. Experimental results show that the precision score and success score of the proposed algorithm are 0.825 and 0.625, which are 18.5% and 31.0% higher than those of the KCF algorithm, respectively. The proposed algorithm can better solve the tracking problems of the target scale variation, occlusion, fast motion, rotation and background clutter, showing a wide range of application prospect.