• Title/Summary/Keyword: 모션 측정

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Implementation of Virtual Realily Immersion System using Motion Vectors (모션벡터를 이용한 가상현실 체험 시스템의 구현)

  • 서정만;정순기
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.3
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    • pp.87-93
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    • 2003
  • The purpose of this research is to develop a virtual reality system which enables to actually experience the virtual reality through the visual sense of human. TSS was applied in tracing the movement of moving picture in this research. By applying TSS, it was possible to calculate multiple motion vectors from moving picture, and then camera's motion parameters were obtained by utilizing the relationship between the motion vectors. For the purpose of experiencing the virtual reality by synchronizing the camera's accelerated velocity and the simulator's movements, the relationship between the value of camera's accelerated velocity and the simulator's movements was analyzed and its result was applied to the neutral network training. It has been proved that the proposed virtual reality immersion system in this dissertation can dynamically control the movements of moving picture and can also operate the simulator quite similarly to the real movements of moving picture.

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Pose Calibration of Inertial Measurement Units on Joint-Constrained Rigid Bodies (관절체에 고정된 관성 센서의 위치 및 자세 보정 기법)

  • Kim, Sinyoung;Kim, Hyejin;Lee, Sung-Hee
    • Journal of the Korea Computer Graphics Society
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    • v.19 no.4
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    • pp.13-22
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    • 2013
  • A motion capture system is widely used in movies, computer game, and computer animation industries because it allows for creating realistic human motions efficiently. The inertial motion capture system has several advantages over more popular vision-based systems in terms of the required space and cost. However, it suffers from low accuracy due to the relatively high noise levels of the inertial sensors. In particular, the accelerometer used for measuring gravity direction loses the accuracy when the sensor is moving with non-zero linear acceleration. In this paper, we propose a method to remove the linear acceleration component from the accelerometer data in order to improve the accuracy of measuring gravity direction. In addition, we develop a simple method to calibrate the joint axis of a link to which an inertial sensor belongs as well as the position of a sensor with respect to the link. The calibration enables attaching inertial sensors in an arbitrary position and orientation with respect to a link.

A Study on Treadmill Interface Technology using Processing of Plantar Pressure Data (족저 압력 데이터 처리를 이용한 가상현실 트레드밀 연구)

  • Cha, Moo-Hyun;Park, Chan-Seok;Jeong, Jin-Gyu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.04a
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    • pp.1064-1065
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    • 2017
  • 트레드밀 인터페이스는 사용자의 보행 모션을 인식하여 가상세계를 네비게이션 할 수 있는 보행 플랫폼이다. 특히 작은 보행 영역을 가지는 트레드밀의 경우, 보행자 속도 예측 방법에 의해 더욱 효과적인 지면 모션의 생성이 가능하다. 본 연구에서는 착용형 압력 센서로 부터 측정되는 족부 압력 데이터를 기반으로 하는 보행속도 예측 방법과 트레드밀 제어 방법을 제시하고자 한다. 속도 예측은 지면 반발력 데이터 중 압력중심의 변화 속도를 통해 도출되며, 예측된 속도를 트레드밀 속도 제어에 안정적으로 적용하기 위한 피드포워드 제어 방법을 제시한다. 또한 족부 압력 데이터 측정이 가능한 자율 제어 트레드밀 시스템 구현과 보행 실험 과정을 소개한다.

Rehabilitation Training System for Leg Rehabilitation based on Motion capture (하지 재활을 위한 모션 캡쳐 기반 재활 훈련 시스템 개발)

  • Kim, Sang-Yun;Jung, Seong-Dae;Kim, Sang-Ho;Jung, Soon-Ki;Lee, Yang-Soo;Kim, Chul-Hyun
    • 한국HCI학회:학술대회논문집
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    • 2007.02a
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    • pp.109-114
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    • 2007
  • 본 논문에서는 하지 편마비 환자의 편마비 정도를 측정하여 사용하지 않으려고 하는 근육을 강제적으로 사용하도록 하여 하지를 재활할 수 있도록 훈련하는 시스템을 제안한다. 제안하는 시스템은 체중 부하 및 하지 슬관절의 움직임을 측정하여, 이를 통해 환자가 자신의 편마비 정도를 인식할 수 있도록 화면에 출력함으로써 환자가 피드백을 통해 강제적으로 편마비 하지를 사용 하도록 훈련 시킬 수 있다. 하지 슬관절(Knee Joint)의 움직임은 기존의 방법과는 달리 적외선 필터를 장착한 단일 카메라를 통한 모션 캡쳐 기술을 사용하여 획득한다. 또한, 재활 시스템에 가상현실 기술을 도입하여 무릎을 동시에 굽혔다가 펴는 기립훈련과 양측 하지를 이용한 보행훈련을 입력으로 가상공간을 탐험할 수 있게 함으로써 환자가 흥미롭게 재활훈련을 받을 수 있도록 하였다.

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Verification of the usefulness of smartphone for wrist swing motion in VR environments (VR 환경에서 손목 스윙 동작에 대한 스마트폰의 유용성 검증)

  • Lee, Chung-Jae;Kim, Jong-Hyun;Lee, Jung;Kim, Sun-Jeong
    • Journal of Korea Game Society
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    • v.17 no.3
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    • pp.53-62
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    • 2017
  • VR content manipulation equipment is not easy for individuals to access because it requires high prices. Especially, in the case of a system for tracking the motion of the user among the VR contents, a separate optical sensor device using an infrared camera is generally used. The disadvantage of the optical sensor equipment is that the measurable range is dependent on the measurement direction when tracking the rotation motion when using only a single device. In order to solve the above problems, this paper shows that the inertial sensor of the smartphone, which is generally owned by the public, can track the rotational motion of the user regardless of the measurement direction . The system using the LeapMotion is used as the reference system, and the system using the smart phone is defined as the evaluation system, and the usability of the evaluation system is verified by comparing the user satisfaction of the two systems.

Analysis of User Head Motion for Motion Classifier of Motion Headset (모션헤드셋의 동작분류기를 위한 사용자 머리동작 분석)

  • Shin, Choonsung;Lee, Youngho
    • Journal of Internet of Things and Convergence
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    • v.2 no.2
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    • pp.1-6
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    • 2016
  • Recently, various types of wearable computers have been studied. In this paper, we analyze the characteristics of head motion information for the operation of the motion classifier produced motion headset that the user can use while listening to music. The prototype receives music from smart phone over bluetooth communications, and transmits the motion information measured by the acceleration sensor to the smart phone. And the smartphone classifies the motion of the head through a motion classifier. we implemented a prototype for our experiment. The user's head motion "up", "down", "left" and "right" were classified using a Bayesian classifier. As a result, in case of the movement of the head "up" and "down", there are a large changes in the x, z-axis values. In future we have a plan to perform a user study to find suitable variables for creating motion classifier.

Real-Time Human Tracker Based Location and Motion Recognition for the Ubiquitous Smart Home (유비쿼터스 스마트 홈을 위한 위치와 모션인식 기반의 실시간 휴먼 트랙커)

  • Park, Se-Young;Shin, Dong-Kyoo;Shin, Dong-Il;Cuong, Nguyen Quoe
    • Proceedings of the Korean Information Science Society Conference
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    • 2008.06d
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    • pp.444-448
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    • 2008
  • The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2:image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

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Real-Time Human Tracker Based on Location and Motion Recognition of User for Smart Home (스마트 홈을 위한 사용자 위치와 모션 인식 기반의 실시간 휴먼 트랙커)

  • Choi, Jong-Hwa;Park, Se-Young;Shin, Dong-Kyoo;Shin, Dong-Il
    • The KIPS Transactions:PartA
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    • v.16A no.3
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    • pp.209-216
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    • 2009
  • The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

Case Analysis of the Promotion Methodologies in the Smart Exhibition Environment (스마트 전시 환경에서 프로모션 적용 사례 및 분석)

  • Moon, Hyun Sil;Kim, Nam Hee;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.171-183
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    • 2012
  • In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

Metamorphosis Hierarchical Motion Vector Estimation Algorithm (변형계층적 모션벡터 추정알고리즘)

  • Kim Jeong-Woong;Yang Hae-Sool
    • Proceedings of the Korea Information Processing Society Conference
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    • 2006.05a
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    • pp.709-712
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    • 2006
  • 다양한 종류의 컴퓨터가 사람, 사물, 환경 속에 내재되어 있고, 이들이 서로 연결되어, 필요한 곳에서 활용할 수 있는 유비쿼터스 환경에서는 홈 네트워크를 통해 이 기종 기기간 다양한 데이터 교환을 요구한다. 더욱이 원활한 영상 데이터의 처리, 전송, 모니터링 기술은 핵심적 요소가 아닐 수 없다. 공간 및 시간적인 해상도, 컬러의 표현 그리고 화질의 측정방법 등 고전적 영상 처리 연구 분야뿐만 아니라 국한된 대역폭을 갖는 홈네트워크의 전송체계에서 전송률 문제에 대한 심도 있는 연구가 필요하다. 본 논문에서는 홈네트워크 상황에서 콘텐츠의 중심이 되는 영상 데이터의 전송과 처리 그리고 제어를 위하여 새로운 움직임 추정 알고리즘을 제안한다. 각도, 거리등 다양한 환경에서 전송되어지는 스테레오 카메라의 영상데이터들은 축소, 확대, 이동, 보정 등 전처리 후 제안된 변형계층 모션벡터 추정 알고리즘을 이용하여 압축 처리, 전송된다. 기존 모션벡터 추정 알고리즘의 장점을 계승하고 단점을 보완한 변형계층 알고리즘은 비정형, 소형 매크로 블록을 이용하여 휘도의 편차가 큰 영상의 효율적 움직임 추정에 이용된다. 본 논문에서 제안한 변형계층 알고리즘과 이를 이용해 구현된 영상시스템은 유비쿼터스 환경에서 다양하게 활용될 수 있다.

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