• Title/Summary/Keyword: MCML(Motion Capture Markup Language)

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Implementation of New Markup Language for Integrating of Motion Capture Data formats (모션 캡쳐 데이타 통합을 위한 새로운 마크업 언어의 구현)

  • 정현숙;이일병
    • Journal of KIISE:Software and Applications
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    • v.30 no.3_4
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    • pp.219-230
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    • 2003
  • Motion capture technology is widely used to make a realistic motion in these days. So, motion capture data is required to exchange between many animators in a work group. But different motion capture devices have different motion rapture data formats. Thus it is difficult that a animator reuse and exchange motion capture data in a storage. In this paper, we proposes a standard format for integrating a different motion capture data format. In addition, we proposes a framework of a system that manage motion capture data using our standard format. Our standard format is called MCML(Motion Capture Markup Language). It is a markup language for motion capture data and based on XML(extensable Markup Language). Our system to manage motion capture data consists of a several component - MCML Converter, MCML , MCML Editor, Motion Viewer.

Storing and Retrieving Motion Capture Data based on Motion Capture Markup Language and Fuzzy Search (MCML 기반 모션캡처 데이터 저장 및 퍼지 기반 모션 검색 기법)

  • Lee, Sung-Joo;Chung, Hyun-Sook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.2
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    • pp.270-275
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    • 2007
  • Motion capture technology is widely used for manufacturing animation since it produces high quality character motion similar to the actual motion of the human body. However, motion capture has a significant weakness due to the lack of an industry wide standard for archiving and retrieving motion capture data. In this paper, we propose a framework to integrate, store and retrieve heterogeneous motion capture data files effectively. We define a standard format for integrating different motion capture file formats. Our standard format is called MCML (Motion Capture Markup Language). It is a markup language based on XML (eXtensible Markup Language). The purpose of MCML is not only to facilitate the conversion or integration of different formats, but also to allow for greater reusability of motion capture data, through the construction of a motion database storing the MCML documents. We propose a fuzzy string searching method to retrieve certain MCML documents including strings approximately matched with keywords. The method can be used to retrieve desired series of frames included in MCML documents not entire MCML documents.

Design & Implementation of a Motion Capture Database Based on Motion Ontologies (온톨로지 기반의 모션 캡처 데이터베이스 설계 및 구현)

  • Chung Hyun-Sook
    • Journal of Korea Multimedia Society
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    • v.8 no.5
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    • pp.618-632
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    • 2005
  • A framework for semantic annotation oi human motion sequences is proposed in this paper. Motion capture technology is widely used for manuiacturing animation since it produces high qualify character motion similar to the actual motion of the human body. However, motion capture has a significant weakness due to the lack of an industry wide standard for archiving and retrieving motion capture data. It is difficult for animators to retrieve the desired motion sequences from motion capture files as there is no semantic annotation on already captured motion data. Our goal is to improve the reusability of motion capture data. To archive our goal first, we propose a standard format for integrating different motion capture file formals. Our standard format is called MCML (Motion Capture Markup Language). It is a markup language based on XML (extensible Markup Language). The purpose of MCML is not only to facilitate the conversion or integration of different formats, but also to allow for greater reusability of motion capture data, through the construction of a motion database storing the MCML documents Second, we define motion ontologies that are used to annotate and semantically organize human motion sequences. This ontology-based approach provides the means for discovering and exploiting the information and knowledge surrounding motion capture data.

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