Abstract: In this paper, we investigate the correction between human motion and garment deformation. First, the features of human motion and garment deformation were defined and extracted. Second, high-resolution garment animations were generated using different types of garment and human motions. The correction between them then was studied based on four machine learning algorithms. Experimental results show that the correlation between garment deformation and human motion is strong, and thus garment deformation distribution can be predicted based on human motion. Compared with BP neural network, generalized regression neural network and support vector machine, random forest method is more effective and more precise, and the final error of random forest is in the ideal range.