• 제목/요약/키워드: 3D human data

검색결과 819건 처리시간 0.03초

단면 분할 FFD를 이용한 3D 라스트 데이터 생성시스템 개발 (Three Dimensional Last Data Generation System Utilizing Cross Sectional Free Form Deformation)

  • 김시경;박인덕
    • 제어로봇시스템학회논문지
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    • 제11권9호
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    • pp.768-773
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    • 2005
  • A new approach for human foot modelling and last design based on the cross sectional method is presented in this paper. The proposed last design method utilizes the dynamic trimmed parametric patches for the foot 3D data and last 3D data. The cross section a surface of 3D foot for the 3D last, design modeling of free form geometric last shapes. The proposed last design scheme wraps the 3D last data surrounding the measured 3D foot data with the effect of deforming the last design rule The last design rule of the FFD is constructed on the FFD lattice based on foot-last shape analysis. In addition, the control points of FFD lattice are constructed with cross sectional data interpolation methods from the a finite set of 3D foot data. The deformed 3D last result obtained from the proposed FFD is saved as a 3D dxf foot data. The experimental results demonstrate that the last designed with the proposed scheme has good performance.

고장 진단 및 예지가 가능한 로봇용 감속기 내구성능평가 장치 개발 (Development of a Lifetime Test Bench for Robot Reducers for Fault Diagnosis and Failure Prognostics)

  • 신주성;김주현;김종걸;김무림
    • 드라이브 ㆍ 컨트롤
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    • 제16권3호
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    • pp.33-41
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    • 2019
  • This study presents the development of a lifetime test bench for the strain wave reducer which is a precision gear reducer of the robot to realize fault diagnosis and failure prognostics. To this end, the lifetime test bench was designed to detect the vertical forward/reverse direction rotation load. Through the lifetime test bench, it is possible to apply the same load spectrum from robot working scenarios. We developed a data integration gateway for fault data collection. Through the development of dedicated software for fault diagnosis and failure prognostics, these data from vibration, noise and temperature sensors were collected and analyzed along with the operation of the lifetime evaluation.

An Evaluation Method of Taekwondo Poomsae Performance

  • Thi Thuy Hoang;Heejune Ahn
    • Journal of information and communication convergence engineering
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    • 제21권4호
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    • pp.337-345
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    • 2023
  • In this study, we formulated a method that evaluates Taekwondo Poomsae performance using a series of choreographed training movements. Despite recent achievements in 3D human pose estimation (HPE) performance, the analysis of human actions remains challenging. In particular, Taekwondo Poomsae action analysis is challenging owing to the absence of time synchronization data and necessity to compare postures, rather than directly relying on joint locations owing to differences in human shapes. To address these challenges, we first decomposed human joint representation into joint rotation (posture) and limb length (body shape), then synchronized a comparison between test and reference pose sequences using DTW (dynamic time warping), and finally compared pose angles for each joint. Experimental results demonstrate that our method successfully synchronizes test action sequences with the reference sequence and reflects a considerable gap in performance between practitioners and professionals. Thus, our method can detect incorrect poses and help practitioners improve accuracy, balance, and speed of movement.

메쉬 간략화를 이용한 3차원 얼굴모델링 (3D Face Modeling Using Mesh Simplification)

  • 이현철;허기택
    • 한국콘텐츠학회논문지
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    • 제3권4호
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    • pp.69-76
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    • 2003
  • 최근 컴퓨터 그래픽스 분야에서는 3차원 애니메이션에 대한 연구가 활발히 이루어지고 있다. 3차원 애니메이션에서 중요한 연구 분야 중 하나가 인간을 애니메이션 하는 것이다. 3차원 얼굴을 이용한 애니메이션 제작은 주로 애니메이터에 의해 수작업으로 해당 프레임별로 작업을 진행하므로 많은 노력과 시간, 해당 장비와 3D 소프트웨어를 필요로 했다. 본 논문에서는 정면 얼굴 이미지를 입력하여 쉽고 빠르게 특정얼굴에 근접한 3D 얼굴모델을 생성하는 방법을 구현하였다. 이를 위해 3D 일반모델의 메쉬 데이터를 간략화 하는 기법에 대해서 제안한다.

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3차원 자세 추정을 위한 딥러닝 기반 이상치 검출 및 보정 기법 (Deep Learning-Based Outlier Detection and Correction for 3D Pose Estimation)

  • 주찬양;박지성;이동호
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제11권10호
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    • pp.419-426
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    • 2022
  • 본 논문에서는 다양한 운동 모션에서 3차원 사람 자세 추정 모델의 정확도를 향상하는 방법을 제안한다. 기존의 사람 자세 추정 모델은 사람의 자세를 추정할 때 좌표 오차를 유발하는 흔들림, 반전, 교환, 오검출 등의 문제가 발생한다. 이러한 문제는 사람 자세 추정 모델의 정확한 자세 추정을 어렵게 한다. 이를 해결하기 위해 본 논문에서는 딥러닝 기반 이상치 검출 및 보정 방법을 제안한다. 딥러닝 기반의 이상치 검출 방법은 여러 모션에서 좌표의 이상치를 효과적으로 검출하고, 모션의 특징을 활용한 규칙 기반 보정 방법을 통해 이상치를 보정한다. 다양한 실험과 분석을 통하여 제안하는 방법이 골프 스윙 모션과 다양한 운동 모션에서도 사람의 자세를 정확히 추정할 수 있고, 3차원 좌표 데이터에서도 확장 가능함을 보인다.

Investigations into the Influencing Fabric Properties Factors of the 3D Shape Evaluation of Korean Hanbok Chima

  • Park, Soon-Jee
    • International Journal of Human Ecology
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    • 제7권1호
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    • pp.37-52
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    • 2006
  • This study was designed to analyze the three-dimensional shapes of Hanbok Chima made with various fabrics and to clarify the relationship between fabric properties as well as the objective and subjective evaluations of the 3D shape. For 3D shape data, a dress form (9A2 (N; nude)) was scanned with eight Chima garments made with the same number of fabrics. The scanner used was a non-contact three-dimensional human body measuring system belonging to Bunka Women's University in Japan. Data concerning the objective evaluation of the 3D shape was obtained from the measurements of the vertical and horizontal sections: those for subjective evaluation were through the sensory test after exposure to photographs from a front and side view. Four fabric factors were extracted from fabric physical properties: softness, extension, thickness of threads, and weight of fabric. Such factors as expansion (volume), sag of rear train, shape of nodes were influential in explaining the 3D shape of Hanbok Chima. From the analysis of the 3D shape, it can be deduced that with the constituent fabric stiffer, lighter, and less stretchable, the more expanded the 3D shape appeared to be. Multiple regression results showed that vertical shape factors have a greater effect on the evaluation of the 3D shape. It also implies that dependent variables of this study such as the subjective evaluation and 3D shape can be derived from regression equations on independent variables as fabric property factors or 3D shape factors. These results can enable the manufacturers to predict the 3D shape of the garment as well as the human subjective assessment to improve the efficacy of production. The investigation method proposed in this study can also be applicable to other garment items.

A Research on Efficient Skeleton Retargeting Method Suitable for MetaHuman

  • Shijie Sun;Ki-Hong Kim;David-Junesok Lee
    • International Journal of Internet, Broadcasting and Communication
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    • 제16권1호
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    • pp.47-54
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    • 2024
  • With the rapid development of 3D animation, MetaHuman is widely used in film production, game development and VR production as a virtual human creation platform.In the animation production of virtual humans, motion capture is usually used.Since different motion capture solutions use different skeletons for motion recording, when the skeleton level of recorded animation data is different from that of MetaHuman, the animation data recorded by motion capture cannot be directly used on MetaHuman. This requires Reorient the skeletons of both.This study explores an efficient skeleton reorientation method that can maintain the accuracy of animation data by reducing the number of bone chains.In the experiment, three skeleton structures, Rokoko, Mixamo and Xsens were used for efficient redirection experiments, to compare and analyze the adaptability of different skeleton structures to the MetaHuman skeleton, and to explore which skeleton structure has the highest compatibility with the MetaHuman skeleton.This research provides an efficient skeleton reorientation idea for the production team of 3D animated video content, which can significantly reduce time costs and improve work efficiency.

Spatial-temporal texture features for 3D human activity recognition using laser-based RGB-D videos

  • Ming, Yue;Wang, Guangchao;Hong, Xiaopeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권3호
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    • pp.1595-1613
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    • 2017
  • The IR camera and laser-based IR projector provide an effective solution for real-time collection of moving targets in RGB-D videos. Different from the traditional RGB videos, the captured depth videos are not affected by the illumination variation. In this paper, we propose a novel feature extraction framework to describe human activities based on the above optical video capturing method, namely spatial-temporal texture features for 3D human activity recognition. Spatial-temporal texture feature with depth information is insensitive to illumination and occlusions, and efficient for fine-motion description. The framework of our proposed algorithm begins with video acquisition based on laser projection, video preprocessing with visual background extraction and obtains spatial-temporal key images. Then, the texture features encoded from key images are used to generate discriminative features for human activity information. The experimental results based on the different databases and practical scenarios demonstrate the effectiveness of our proposed algorithm for the large-scale data sets.

인체 전신 레이저 스캔 데이터를 대상으로 한 인체 애니메이션 연구 (A Study for Animation Using 3D Laser Scanned Body Data)

  • 윤근호;조창석
    • 한국멀티미디어학회논문지
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    • 제15권10호
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    • pp.1257-1263
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    • 2012
  • 본 연구는 3D레이저 스캔 방식으로 계측된 인체 데이터를 대상으로 하여 인체의 여러 동작들에 대한 애니메이션 모듈 구현을 목표로 하였다. 이를 위하여 애니메이션 회전을 위한 기준점인 인체의 골격 기준점을 추출하고 추출된 기준점을 이용하여 골격을 잡고 각 골격에 따른 계층트리를 구성하였다. 구성된 계층트리의 골격에 해당되는 오브젝트 정점들을 골격과 연결하고 주어진 애니메이션 3차원 정점들에 행동 패턴을 적용하여 스캔데이터에 애니메이션을 구현하였다.