The traditional three-dimensional (3D) model classification method relies on the overall shape characteristics of cultural relics, which causes the problem of low efficiency, high cost and low accuracy for the classification of cultural debris with serious damage, missing details and irregular shapes. The depth information of local surface around the feature points of cultural relics and the regular geometric texture of the surface can be used as the discriminative features of classification. Therefore, a local point cloud information and significant multi-feature descriptor are proposed. The surface regularity geometric feature, combined with the rotation projection feature, are used as the discriminant features of the classification of cultural relics; then the similarity metric rule is proposed and the weight of two characteristics are adaptively calculated according to the measurement results of each type of feature, to achieve the classification of cultural debris. The debris data set of terracotta warriors is used as experimental data for the classification, the results show that the proposed method occupies small memory and calculates fast. Multiple cross-validation methods are used to verify the results, the accuracy rate is 74.78%, which is 15.64% higher than that of the traditional 3D model matching method.