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基于差异特征协同语义标注的三维模型检索方法

     

摘要

提出一种基于差异特征协同语义标注的三维模型检索方法.该方法利用多种特征提取方法的优点,借鉴半监督学习中的协同训练思想,首先通过3种差异特征提取算法分别训练学习器,构造出3个差异学习器;然后通过协同迭代训练找到最优学习器对三维模型进行自动语义标注;最后结合语义进行三维模型检索.在普林斯顿大学的PSB三维模型数据集上的实验结果表明,该方法的语义标注准确率优于单一特征提取方法,同时三维模型的查全率和查准率获得了较显著的提高.%A 3D models retrieval method based on collaboration semantic annotation of discrepant feature is proposed. The method makes use of advantage of several feature extraction algorithms, and refers collaborative training approach in semi-supervised learning. Firstly, three classifiers by are trained with different feature extraction algorithms respectively, and three different classifiers are constructed. Secondly, 3D models are semantic annotated with semantics automatically by the optimal classifier which was found during the course of collaborative iterative training. Finally, 3D models retrieval with semantics is carried out. Experiments on PSB show that the annotation accuracy of this method is higher than the method based on single-feature. Meanwhile, the recall-precision rises.

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