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    向 坚, 郭同强, 吴 飞, 庄越挺, 叶 绿. 基于双向参考索引的大规模人体运动数据库的检索[J]. 计算机研究与发展, 2008, 45(12): 2145-2153.
    引用本文: 向 坚, 郭同强, 吴 飞, 庄越挺, 叶 绿. 基于双向参考索引的大规模人体运动数据库的检索[J]. 计算机研究与发展, 2008, 45(12): 2145-2153.
    Xiang Jian, Guo Tongqiang, Wu Fei, Zhuang Yueting, Ye Lü. Motion Retrieval Based on Large-Scale 3D Human Motion Database by Double-Reference Index[J]. Journal of Computer Research and Development, 2008, 45(12): 2145-2153.
    Citation: Xiang Jian, Guo Tongqiang, Wu Fei, Zhuang Yueting, Ye Lü. Motion Retrieval Based on Large-Scale 3D Human Motion Database by Double-Reference Index[J]. Journal of Computer Research and Development, 2008, 45(12): 2145-2153.

    基于双向参考索引的大规模人体运动数据库的检索

    Motion Retrieval Based on Large-Scale 3D Human Motion Database by Double-Reference Index

    • 摘要: 因为运动特征数据的高维复杂性,采用非线性的Isomap流形学习的降维算法来对运动特征数据进行降维,为了能让Isomap方法处理训练数据集之外的数据,通过学习主成分特征核函数逼近降维结果,以扩展传统Isomap的局限性.在运动数据降维之后,为大规模运动捕获数据库建立一种双向参考索引(DRI),在检索过程中索引用来排除绝大部分与查询例子无关的运动数据,这样运动检索中的相似度的计算通过索引被缩小到一个小范围候选数据集合中,避免了大量不必要的匹配开销,从而提高了检索的效率.

       

      Abstract: In this paper, a novel approach is presented for motion retrieval based on double-reference index that reduces the number of costly distance computations for similarity measure. In order to retrieve motion data accurately, the features about joint positions, angles and velocities are extracted to represent motion data. Since these original features of motion clips lie in high-dimensional space and on a high-dimensional manifold, which is highly contorted, the Isomap nonlinear dimension reduction is used to map them into low-dimensional manifold. However, geo-distance of Isomap is only defined on training sets and raw Isomap cannot map new samples to the embedding subspace because it requires a whole set of points in the database to calculate geo-distance. For handling out-of-samples motion data, Isomap is generalized based on the estimation of underlying eigenfunctions. Then the methold of double-reference index(DRI) is proposed based on selecting a small set of representative motion clips in the database. So it can get candidate set by abandoning most unrelated motion clips to reduce the number of costly similarity measure significantly. Finally the automatic method is tested on a large collection of motion capture clips with a large variety of actions. Experiment results show that the proposed methods are effective for motion data retrieval in large-scale database.

       

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