• Title/Summary/Keyword: 모션 캡처 데이터

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Trajectory Rectification of Marker using Confidence Model (신뢰도 모델을 이용한 마커 궤적 재조정)

  • Ahn, Junghyun;Jang, Mijung;Wohn, Kwangyun
    • Journal of the Korea Computer Graphics Society
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    • v.8 no.3
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    • pp.17-23
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    • 2002
  • Motion capture system is widely used nowadays in the entertainment industry like movies, computer games and broadcasting. This system consist of several high resolution and high speed CCD cameras and expensive frame grabbing hardware for image acquisition. KAIST VR laboratory focused on low cost system for a few years and have been developed a LAN based optical motion capture system. But, by using low cost system some problems like occlusion, noise and swapping of markers' trajectory can be occurred. And more labor intensive work is needed for post-processing process. In this thesis, we propose a trajectory rectification algorithm by confidence model of markers attached on actor. Confidence model is based on graph structure and consist of linkage, marker and frame confidence. To reduce the manual work in post-processing, we have to reconstruct the marker graph by maximizing the frame confidence.

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A Study on Sensor-Based Upper Full-Body Motion Tracking on HoloLens

  • Park, Sung-Jun
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.4
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    • pp.39-46
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    • 2021
  • In this paper, we propose a method for the motion recognition method required in the industrial field in mixed reality. In industrial sites, movements (grasping, lifting, and carrying) are required throughout the upper full-body, from trunk movements to arm movements. In this paper, we use a method composed of sensors and wearable devices that are not vision-based such as Kinect without using heavy motion capture equipment. We used two IMU sensors for the trunk and shoulder movement, and used Myo arm band for the arm movements. Real-time data coming from a total of 4 are fused to enable motion recognition for the entire upper body area. As an experimental method, a sensor was attached to the actual clothes, and objects were manipulated through synchronization. As a result, the method using the synchronization method has no errors in large and small operations. Finally, through the performance evaluation, the average result was 50 frames for single-handed operation on the HoloLens and 60 frames for both-handed operation.

Learning Multi-Character Competition in Markov Games (마르코프 게임 학습에 기초한 다수 캐릭터의 경쟁적 상호작용 애니메이션 합성)

  • Lee, Kang-Hoon
    • Journal of the Korea Computer Graphics Society
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    • v.15 no.2
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    • pp.9-17
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    • 2009
  • Animating multiple characters to compete with each other is an important problem in computer games and animation films. However, it remains difficult to simulate strategic competition among characters because of its inherent complex decision process that should be able to cope with often unpredictable behavior of opponents. We adopt a reinforcement learning method in Markov games to action models built from captured motion data. This enables two characters to perform globally optimal counter-strategies with respect to each other. We also extend this method to simulate competition between two teams, each of which can consist of an arbitrary number of characters. We demonstrate the usefulness of our approach through various competitive scenarios, including playing-tag, keeping-distance, and shooting.

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Design of Avatar Rehabilitation Content Service with Limited Range of Motion (관절 가동 범위의 제한 정보를 반영한 아바타 기반 재활 운동 콘텐츠 서비스 설계)

  • Yoon, Chang-Rak;Chang, Yoon-Seop;Kim, Jae-Chul
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.990-992
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    • 2021
  • 근골격계 질환 환자들은 정상인들에 비해 질환 부위의 관절 가동 범위(ROM, Range of Motion)가 제한되는 경향이 있다. 이러한 근골격계 질환 환자들의 관절 가동 범위 제한을 고려하지 않은 재활 운동 콘텐츠 서비스는 오히려 환자의 건강 상태를 악화시킬 수도 있으므로 주의해야 하는 서비스 요인이다. 본 논문에서는 근골격계 질환 환자의 제한적인 관절 가동 범위를 고려한 아바타 기반의 재활 운동 콘텐츠 서비스 기술을 제안한다. 이에 재활 운동의 모션 캡처 데이터로부터 아바타 재활 운동 콘텐츠로의 변환 기술과 근골격계 질환 환자의 관절 가동 범위 제한 정보를 적용한 아바타 기반 재활 운동 콘텐츠 재현 기술을 설계한다. 일련의 기술적 구성 요소를 고찰하고 설계함으로써 근골격계 질환 환자들의 서로 다른 관절 가동 범위를 반영한 맞춤형 재활 운동 콘텐츠 서비스가 안전하고 효과적인 재활을 지원할 수 있도록 한다.

3D Rigid Body Tracking Algorithm Using 2D Passive Marker Image (2D 패시브마커 영상을 이용한 3차원 리지드 바디 추적 알고리즘)

  • Park, Byung-Seo;Kim, Dong-Wook;Seo, Young-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.587-588
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    • 2022
  • In this paper, we propose a rigid body tracking method in 3D space using 2D passive marker images from multiple motion capture cameras. First, a calibration process using a chess board is performed to obtain the internal variables of individual cameras, and in the second calibration process, the triangular structure with three markers is moved so that all cameras can observe it, and then the accumulated data for each frame is calculated. Correction and update of relative position information between cameras. After that, the three-dimensional coordinates of the three markers were restored through the process of converting the coordinate system of each camera into the 3D world coordinate system, the distance between each marker was calculated, and the difference with the actual distance was compared. As a result, an error within an average of 2mm was measured.

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A Motion-driven Rowing Game based on Teamwork of Multiple Players (다중 플레이어들의 팀워크에 기반한 동작-구동 조정 게임)

  • Kim, Hyejin;Shim, JaeHyuk;Lim, Seungchan;Goh, Youngnoh;Han, Daseong
    • Journal of the Korea Computer Graphics Society
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    • v.24 no.3
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    • pp.73-81
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    • 2018
  • In this paper, we present a motion-driven rowing simulation framework that allows multiple players to row a boat together by their harmonized movements. In the actual rowing game, it is crucial for the players to synchronize their rowing with respect to time and pose so as to accelerate the boat. Inspired by this interesting feature, we measure the motion similarity among multiple players in real time while they are doing rowing motions and use it to control the velocity of the boat in a virtual environment. We also employ game components such as catching an item which can accelerate or decelerate the boat depending on its type for a moment once it has been obtained by synchronized catching behaviors of the players. By these components, the players can be encouraged to more actively participate in the training for a good teamwork to produce harmonized rowing movements Our methods for the motion recognition for rowing and item catch require the tracking data only for the head and the both hands and are fast enough to facilitate the real-time performance. In order to enhance immersiveness of the virtual environment, we project the rowing simulation result on a wide curved screen.

The Prediction System of Emotional Reaction to Gaits Using MAX SCRIPT (맥스 스크립트를 이용한 감성적 걸음걸이 예측 시스템)

  • Jeong, Jae-Wook
    • Science of Emotion and Sensibility
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    • v.14 no.1
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    • pp.1-6
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    • 2011
  • A perceptual reaction to human being's gaits has "regularity" that possibly obtains sympathy among people. This thesis is in the vein of the study that performs the research on the quantificational extraction of the regularity, reconstitute the result, and apply it to controlling behavior. The purpose of this thesis lies in assuring the validity of the future research by demonstrating the following hypothesis: when the physical numerical values of the gait "A" whose perceptual reaction is "a" and those of the gait "B" whose perceptual reaction is "b" are arbitrarily blended, the perceptual reaction to this blended gait also corresponds to the blend of "a" and "b", "a/b". I blended the samples of two types of gaits in the form of Bipeds using the EAM made by 3D Studio Max Script. Blending outcomes were obtained successfully for four times out of the six tries in total. It implies that without utilizing other methods such as Motion Capturing, the basic Bipeds data itself has an enough capability to generate various gaits of Bipeds. Although the present research targets only the Bipeds samples equipped with the 1Cycle moving condition of arms and legs, I acknowledge that a tool that makes blending possible under various moving conditions is necessary for a completed system.

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FBX Format Animation Generation System Combined with Joint Estimation Network using RGB Images (RGB 이미지를 이용한 관절 추정 네트워크와 결합된 FBX 형식 애니메이션 생성 시스템)

  • Lee, Yujin;Kim, Sangjoon;Park, Gooman
    • Journal of Broadcast Engineering
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    • v.26 no.5
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    • pp.519-532
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    • 2021
  • Recently, in various fields such as games, movies, and animation, content that uses motion capture to build body models and create characters to express in 3D space is increasing. Studies are underway to generate animations using RGB-D cameras to compensate for problems such as the cost of cinematography in how to place joints by attaching markers, but the problem of pose estimation accuracy or equipment cost still exists. Therefore, in this paper, we propose a system that inputs RGB images into a joint estimation network and converts the results into 3D data to create FBX format animations in order to reduce the equipment cost required for animation creation and increase joint estimation accuracy. First, the two-dimensional joint is estimated for the RGB image, and the three-dimensional coordinates of the joint are estimated using this value. The result is converted to a quaternion, rotated, and an animation in FBX format is created. To measure the accuracy of the proposed method, the system operation was verified by comparing the error between the animation generated based on the 3D position of the marker by attaching a marker to the body and the animation generated by the proposed system.

A Study on Korean Speech Animation Generation Employing Deep Learning (딥러닝을 활용한 한국어 스피치 애니메이션 생성에 관한 고찰)

  • Suk Chan Kang;Dong Ju Kim
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.10
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    • pp.461-470
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    • 2023
  • While speech animation generation employing deep learning has been actively researched for English, there has been no prior work for Korean. Given the fact, this paper for the very first time employs supervised deep learning to generate Korean speech animation. By doing so, we find out the significant effect of deep learning being able to make speech animation research come down to speech recognition research which is the predominating technique. Also, we study the way to make best use of the effect for Korean speech animation generation. The effect can contribute to efficiently and efficaciously revitalizing the recently inactive Korean speech animation research, by clarifying the top priority research target. This paper performs this process: (i) it chooses blendshape animation technique, (ii) implements the deep-learning model in the master-servant pipeline of the automatic speech recognition (ASR) module and the facial action coding (FAC) module, (iii) makes Korean speech facial motion capture dataset, (iv) prepares two comparison deep learning models (one model adopts the English ASR module, the other model adopts the Korean ASR module, however both models adopt the same basic structure for their FAC modules), and (v) train the FAC modules of both models dependently on their ASR modules. The user study demonstrates that the model which adopts the Korean ASR module and dependently trains its FAC module (getting 4.2/5.0 points) generates decisively much more natural Korean speech animations than the model which adopts the English ASR module and dependently trains its FAC module (getting 2.7/5.0 points). The result confirms the aforementioned effect showing that the quality of the Korean speech animation comes down to the accuracy of Korean ASR.