Abstract: Feature-based model retrieval is one of the important research directions in the field of computer vision. It includes two aspects: feature extraction and model retrieval. The robustness of features plays a decisive role in model retrieval algorithm. In order to solve the problem of low efficiency of local features in existing algorithms, a feature fusion based model retrieval algorithm for the fragment of terracotta warriors is proposed. Aiming at the 3D point cloud model of the terracotta warriors fragments, the curvature and normal angle of the points on the fragment point cloud model are calculated and fused weighted firstly. Then, the feature matching algorithm is constructed based on the fusion feature, and the 3D fragment model retrieval is realized by matching the fusion feature. In the experiment, 1036 fragments of 50 terracotta warriors are retrieved. The results show that the algorithm can effectively improve the retrieval accuracy of fragments and avoid the algorithm falling into local extremum. Therefore, the 3D model retrieval algorithm based on feature fusion is an effective method to retrieve the fragments of terracotta warriors.