基于图深度学习的Mocap数据检索方法

Graph Deep Learning for Motion Capture Data Retrieval

提出了一种基于图深度学习模型的Mocap数据检索方法。具体而言,首先以Mocap数据中的关节信息和骨骼信息建立图深度学习模型来提取人体动作的深度特征。然后根据图深度学习模型所得到Mocap数据的特征向量训练核函数,最后利用核匹配方法将被检索的Mocap样本数据与Mocap数据集中的数据进行相似度的计算从而完成检索任务。实验表明,此方法优于其他检索方法。

This paper proposes a novel method for Mocap data retrieval based on a graph deep learning model. Firstly, the information of vertices and bones extracted from Mocap data is as input to construct a graph deep learning model for obtaining human motion deep features. Then, a kernel function is trained using the feature vectors learned from the graph deep learning model. Finally, kernel matching method is applied to measure the similarity between query sample and samples in dataset for retrieving target data.