• Title/Summary/Keyword: Virtual Skeleton model

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DOVE : A Distributed Object System for Virtual Computing Environment (DOVE : 가상 계산 환경을 위한 분산 객체 시스템)

  • Kim, Hyeong-Do;Woo, Young-Je;Ryu, So-Hyun;Jeong, Chang-Sung
    • Journal of KIISE:Computing Practices and Letters
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    • v.6 no.2
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    • pp.120-134
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    • 2000
  • In this paper we present a Distributed Object oriented Virtual computing Environment, called DOVE which consists of autonomous distributed objects interacting with one another via method invocations based on a distributed object model. DOVE appears to a user logically as a single virtual computer for a set of heterogeneous hosts connected by a network as if objects in remote site reside in one virtual computer. By supporting efficient parallelism, heterogeneity, group communication, single global name service and fault-tolerance, it provides a transparent and easy-to-use programming environment for parallel applications. Efficient parallelism is supported by diverse remote method invocation, multiple method invocation for object group, multi-threaded architecture and synchronization schemes. Heterogeneity is achieved by automatic data arshalling and unmarshalling, and an easy-to-use and transparent programming environment is provided by stub and skeleton objects generated by DOVE IDL compiler, object life control and naming service of object manager. Autonomy of distributed objects, multi-layered architecture and decentralized approaches in hierarchical naming service and object management make DOVE more extensible and scalable. Also,fault tolerance is provided by fault detection in object using a timeout mechanism, and fault notification using asynchronous exception handling methods

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Analysis on Lower Body Type and 3D Virtual Appearance Evaluation of Boots cut Jeans for Women (성인여성의 하반신 체형분석 및 부츠 컷 청바지의 가상 외관평가)

  • Choi, Jin;Do, Wol-Hee
    • Journal of the Korean Home Economics Association
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    • v.46 no.2
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    • pp.73-83
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    • 2008
  • The focus of this research was concerned with studying lower body type for Korean adult females. information from the measuring values based on research on the physical standard of the nation(2004) were summarized, in addition a factor of the need for appropriate fit in boots cut jean wear, basic lower body part applying to each item had to be taken into consideration to enhance sizing suitability. The body type are classified into three kinds by means of factor analysis and cluster analysis. Type 1 referred to the fat lower body, having thick rounding waist. compared to other body parts, and long leg according to its proportion. Type 2 represented medium stature but with a large skeleton structure of lower body. Type 3 represented a the long lower body having slender rounding waist. This study was attempted to evaluate the fitness of boots cut jeans pattern for women using 3D Clothes Modeling Software.

Real-Time Joint Animation Production and Expression System using Deep Learning Model and Kinect Camera (딥러닝 모델과 Kinect 카메라를 이용한 실시간 관절 애니메이션 제작 및 표출 시스템 구축에 관한 연구)

  • Kim, Sang-Joon;Lee, Yu-Jin;Park, Goo-man
    • Journal of Broadcast Engineering
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    • v.26 no.3
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    • pp.269-282
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    • 2021
  • As the distribution of 3D content such as augmented reality and virtual reality increases, the importance of real-time computer animation technology is increasing. However, the computer animation process consists mostly of manual or marker-attaching motion capture, which requires a very long time for experienced professionals to obtain realistic images. To solve these problems, animation production systems and algorithms based on deep learning model and sensors have recently emerged. Thus, in this paper, we study four methods of implementing natural human movement in deep learning model and kinect camera-based animation production systems. Each method is chosen considering its environmental characteristics and accuracy. The first method uses a Kinect camera. The second method uses a Kinect camera and a calibration algorithm. The third method uses deep learning model. The fourth method uses deep learning model and kinect. Experiments with the proposed method showed that the fourth method of deep learning model and using the Kinect simultaneously showed the best results compared to other methods.