Data-driven automatic generation of decision tree for motion retrieval with temporal-spatial features

被引：0
|
作者：
Xiang, Jian [1 ]
Zhuang, Yue-Ting [1 ]
Wu, Fei [1 ]
机构：
[1] Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Peoples R China
来源：
PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2006年
基金：
中国国家自然科学基金;
关键词：
Motion Capture; 3D temporal-spatial; data driven; decision tree; motion retrieval;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Along with the development of Motion Capture technique, more and more 3D motion libraries become available. In this paper, a novel approach is presented for motion retrieval based on data-driven decision tree with 3D temporal-spatial features. First 3D temporal-spatial features of each human joint are extracted with the help of keyspace. Since the gotten features of each joint are independent, data-driven decision tree is automatically constructed to reflect the influence of each point during the comparison of motion similarity. Experiment results show that the approaches are effective for motion data retrieval.
引用
收藏
页码：2718 / +
页数：3
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