Bo Jin
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Underlying semantic annotation method for human motion capture data
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Indexed by:期刊论文

Date of Publication:2011-01-01

Journal:Information Technology Journal

Included Journals:EI、Scopus

Volume:10

Issue:10

Page Number:1957-1963

ISSN No.:18125638

Abstract:On the issue of the representation model of the human motion 3D series, the most widely used methods were always based on numerical data. These methods could reduce the high dimensional 3D capture motion data and decrease the time complexity to a certain extent. However, the above mentioned traditional methods cannot extract the hidden useful domain physical knowledge, as well as meet the demands of current an intelligent computer processing on the numerical sequence. The present study proposed a new semantic annotation approach to obtain the linguistic tags on 3D motion data. Pre-processing on the human joint information should be implemented to appropriately achieve the spatio-temporal feature. The steps included: Constructing the human motion semantic category space, clustering the intermediate data through merging the kinematics knowledge and finally gaining the semantic annotations. At the end of the present study, the experiments showed that the proposed semantic approach could reasonably express the semantic information. In addition, there was also no absence of the essential domain knowledge of human motion data in the proposed method. ? 2011 Asain Network for Scientific Information.

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Gender:Male

Alma Mater:Dalian University of Technology

Degree:Doctoral Degree

School/Department:Dalian University of Technology

Discipline:Computer Applied Technology

Business Address:816 Yanjiao Building, Dalian University of Technology

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