• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.177-180
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• 2005

오늘날 디지털 비디오 처리 시스템의 성능 향상 및 분석을 위한 많은 방법론이 연구되어 왔지만, 저차원 레벨의 성분에 기반을 둔 것이 일반적이다. 그러나 사용자의 요구는 단순한 저차원의 인식이 아니라 비디오 데이터 내에 포함된 의미를 이해하는 것으로 고차원 레벨의 의미 분석 방법론이 대두되고 있다. 이에 본 논문에서는 객체간 시공간적(Spatio-Temporal) 관계 모델에 기반한 움직임의 메타데이터에 대한 의미적 공간을 생성하기 위해 모션 온톨로지(Motion Ontology)를 제안한다. 이는 의미 기반 비디오 검색을 위한 프레임워크를 제공할 뿐만아니라 자동 나레이션 생성 등에 이용할 수 있을 것이다.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.117-127
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• 2007

As the value of the multimedia data is getting high, the study on the semantic recognition and retrieval about the multimedia information is strongly demanded. In this paper, we build the motion ontology and adopt it for representing the meaning of the moving objects in video data. By referencing the WordNet structure, we extend its semantic meaning based on the reclassification of motion verbs, which are used to represent the semantic meaning of moving objects. The represented information is receded in OWL/RDF(S). Here, we could expect the 'Is-A' and 'Equivalent' reasoning of the data as we use the ontologies. And the semantic representation about the moving objects is possible through the video annotation using ontology. And we tested the accuracy of the system comparing with the key-word based system. As a result, we could get the approximately 10% improvement of the system performance.