Title :
Data-Driven Automatic Generation of Decision Tree for Motion Retrieval with Temporal-Spatial Features
Author :
Xiang, Jian ; Zhuang, Yue-ting ; Wu, Fei
Author_Institution :
Coll. of Comput. Sci., Zhejiang Univ., Hangzhou
Abstract :
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
Keywords :
decision trees; feature extraction; image motion analysis; image retrieval; temporal databases; visual databases; 3D motion library; 3D temporal-spatial feature extraction; data-driven automatic decision tree generation; human joint feature extraction; motion capture technique; motion data retrieval; motion similarity; Computer science; Cybernetics; Data mining; Data processing; Decision trees; Educational institutions; Feature extraction; Humans; Information retrieval; Joints; Machine learning; Motion measurement; 3D Temporal-Spatial; Data Driven; Decision Tree; Motion Capture; Motion Retrieval;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258987
