• Title/Summary/Keyword: 동작 추정

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Operating principle and Analysis for modeling Experimental characterization of Non-aqueous lithium-air battery (비수계 리튬에어 배터리 동작원리와 모델링을 위한 특성실험 분석)

  • Jang, So-Hee;Kim, Jong-Hoon;Choi, Sang-won;Tak, Yong-sug
    • Proceedings of the KIPE Conference
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    • 2016.07a
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    • pp.375-376
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    • 2016
  • 본 논문에서는 Li-air 배터리의 동작원리를 설명하고, 모델링을 위해 Li-air 배터리의 내부와 충전 및 방전 원리를 보여주고 SOC(State Of Charge) 추정을 위한 OCV(Open-circuit Voltage) 그래프의 분석과 회로도에 대해 설명 하였다. 더불어, 전류적산법의 원리를 적용하여 SOC 추정의 기준이 되는 값을 추출하였다.

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An Efficient Clock Cycle Reducing Architecture in Full-Search Block Matching Motion Estimation VLSI (전탐색 블럭정합 움직임추정 VLSI 에서 클럭사이클수를 줄이는 효율적 구조)

  • 윤종성;장순화
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.259-262
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    • 2000
  • 본 논문은 전탐색 블럭매칭 움직임추정 VLSI 구조에서 클럭당 두연산(하나는 클럭의 상향에지, 하나는 하향에지에서 동작)을 수행하는 PE(Processing Element)를 교번적으로 결선, 클럭의 상향에지는 물론 하향에지에서도 동작하도록 하는 방식으로 클럭 사이클수를 줄이는 VLSI 구조를 제안한다 기존 구조에 그대로 적용되는 본 방법은 공급 데이타폭이 2 배, PE 의 HW 복잡도가 1.5 배 절대차 합 연산의 복잡도가 2 배로 늘어나 전체 하드웨어가 복잡해지나, PE수를 2배로 하여 클럭사이클수를 줄이는 방법에 비해서는 매우 효율적이다. 본 제안 구조는 계층적 움직임 추정 알고리듬을 사용한 MPEG-2 움직임 추정기 개발의 설계에 적용하여 기능과 HW 복잡도를 확인하였다.

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Worker Recognition of using on Frame Difference (프레임간 차이를 이용한 작업자 인식)

  • Min Hye-Lan;Lee Joon;Lee Jeong-Gi
    • Proceedings of the Korea Contents Association Conference
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    • 2005.11a
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    • pp.485-489
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    • 2005
  • 본 연구에서는 작업자의 일정한 동작을 보다 효율적으로 인식할 수 있는 시스템을 제안하고자 한다. 먼저, 작업자의 동작을 촬영한 동영상에서 연속된 프레임간의 차를 기반으로, 고정된 배경과 움직이는 대상을 분리한다. 다음으로, 에지 검출을 이용하여 동작의 중심 위치를 추정하여 연속적으로 움직이는 동작을 인식할 수 있도록 하였다. 본 연구에서 설계한 동작 인식시스템은 기존의 산업현장에서 적용되고 있는 동작인식 시스템의 문제점을 보완하기 위하여 작업자의 동작을 고정된 CCTV 로 촬영한 영상을 인식의 대상으로 취함으로써 동작 정보를 얻기 위한 각종 장비들이 최소화되었다. 또한, 작업자의 신체 부분별 특성을 추출하기 위한 계산작업에 소요되는 시간을 줄이기 위하여 프레임간의 차연산과 에지검출을 통한 동작인식을 실시하여 인식에 필요한 작업시간을 단축하여, 효율적이면서 비용이 저렴한 동작 인식시스템을 설계하였다.

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Vision-Based Trajectory Tracking Control System for a Quadrotor-Type UAV in Indoor Environment (실내 환경에서의 쿼드로터형 무인 비행체를 위한 비전 기반의 궤적 추종 제어 시스템)

  • Shi, Hyoseok;Park, Hyun;Kim, Heon-Hui;Park, Kwang-Hyun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39C no.1
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    • pp.47-59
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    • 2014
  • This paper deals with a vision-based trajectory tracking control system for a quadrotor-type UAV for entertainment purpose in indoor environment. In contrast to outdoor flights that emphasize the autonomy to complete special missions such as aerial photographs and reconnaissance, indoor flights for entertainment require trajectory following and hovering skills especially in precision and stability of performance. This paper proposes a trajectory tracking control system consisting of a motion generation module, a pose estimation module, and a trajectory tracking module. The motion generation module generates a sequence of motions that are specified by 3-D locations at each sampling time. In the pose estimation module, 3-D position and orientation information of a quadrotor is estimated by recognizing a circular ring pattern installed on the vehicle. The trajectory tracking module controls the 3-D position of a quadrotor in real time using the information from the motion generation module and pose estimation module. The proposed system is tested through several experiments in view of one-point, multi-points, and trajectory tracking control.

Hand Gesture Interface Using Mobile Camera Devices (모바일 카메라 기기를 이용한 손 제스처 인터페이스)

  • Lee, Chan-Su;Chun, Sung-Yong;Sohn, Myoung-Gyu;Lee, Sang-Heon
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.5
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    • pp.621-625
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    • 2010
  • This paper presents a hand motion tracking method for hand gesture interface using a camera in mobile devices such as a smart phone and PDA. When a camera moves according to the hand gesture of the user, global optical flows are generated. Therefore, robust hand movement estimation is possible by considering dominant optical flow based on histogram analysis of the motion direction. A continuous hand gesture is segmented into unit gestures by motion state estimation using motion phase, which is determined by velocity and acceleration of the estimated hand motion. Feature vectors are extracted during movement states and hand gestures are recognized at the end state of each gesture. Support vector machine (SVM), k-nearest neighborhood classifier, and normal Bayes classifier are used for classification. SVM shows 82% recognition rate for 14 hand gestures.

A study on Estimation of Energy Expenditure using Horseback Riding Simulator (승마 시뮬레이터를 이용한 운동 시 에너지 소모량 추정에 관한 연구)

  • Park, Seongbin;Hyeong, Chun-Ho;Kim, Sayup;Chung, Kyung-Ryul
    • Transactions of the KSME C: Technology and Education
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    • v.1 no.2
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    • pp.193-198
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    • 2013
  • The horseback riding simulator, an exercise training machine providing a simplified horse riding motion has been developed for aiming at healthcare. The purpose of this study was to estimate the energy expenditure without measuring bio-signals using the simulator. The test protocol was consisted of increase up to maximal intensity(Motion 9) and decrease down to minimal intensity(Motion 4) during 25 minutes, and energy expenditure was measured by portable cardiopulmonary exercise testing analyzer. There were significant differences in energy expenditure according to each riding motion. The result will be able to estimate energy expenditure using motion level, exercise time, age and gender during the riding.

Pose Creation of Character in Two-Dimensional Cartoon through Human Pose Estimation (인간자세 추정방법에 의한 2차원 웹툰 캐릭터 포즈 생성)

  • Jeong, Hieyong;Shin, Choonsung
    • Journal of Broadcast Engineering
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    • v.27 no.5
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    • pp.718-727
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    • 2022
  • The Korean domestic cartoon industry has grown explosively by 65% compared to the previous year. Then the market size is expected to exceed KRW 1 trillion. However, excessive work results in health deterioration. Moreover, this working environment makes the production of human resources insufficient, repeating a vicious cycle. Although some tasks require creation activity during cartoon production, there are still a lot of simple repetitive tasks. Therefore, this study aimed to develop a method for creating a character pose through human pose estimation (HPE). The HPE is to detect key points for each joint of a user. The primary role of the proposed method was to make each joint of the character match that of the human. The proposed method enabled us to create the pose of the two-dimensional cartoon character through the results. Furthermore, it was possible to save the static image for one character pose and the video for continuous character pose.

Entropy-based Discrimination of Hand and Elbow Movements Using ECoG Signals (엔트로피 기반 ECoG 신호를 이용한 손과 팔꿈치 움직임 추론)

  • Kim, Ki-Hyun;Cha, Kab-Mun;Rhee, Kiwon;Chung, Chun Kee;Shin, Hyun-Chool
    • Journal of IKEEE
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    • v.17 no.4
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    • pp.505-510
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    • 2013
  • In this paper, a method of estimating hand and elbow movements using electrocorticogram (ECoG) signals is proposed. Using multiple channels, surface electromyogram (EMG) signals and ECoG signals were obtained from patients simultaneously. The estimated movements were those to close and then open the hand and those to bend the elbow inward. The patients were encouraged to perform the movements in accordance with their free will instead of after being induced by external stimuli. Surface EMG signals were used to find movement time points, and ECoG signals were used to estimate the movements. To extract the characteristics of the individual movements, the ECoG signals were divided into a total of six bands (the entire band and the ${\delta}$, ${\Theta}$, ${\alpha}$, ${\beta}$, and ${\gamma}$ bands) to obtain the information entropy, and the maximum likelihood estimation method was used to estimate the movements. The results of the experiment showed the performance averaged 74% when the ECoG of the gamma band was used, which was higher than that when other bands were used, and higher estimation success rates were shown in the gamma band than in other bands. The time of the movements was divided into three time sections based on movement time points, and the "before" section, which included the readiness potential, was compared with the "onset" section. In the "before" section and the "onset" section, estimation success rates were 66% and 65%, respectively, and thus it was determined that the readiness potential could be used.

Occluded Object Motion Tracking Method based on Combination of 3D Reconstruction and Optical Flow Estimation (3차원 재구성과 추정된 옵티컬 플로우 기반 가려진 객체 움직임 추적방법)

  • Park, Jun-Heong;Park, Seung-Min;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.5
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    • pp.537-542
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    • 2011
  • A mirror neuron is a neuron fires both when an animal acts and when the animal observes the same action performed by another. We propose a method of 3D reconstruction for occluded object motion tracking like Mirror Neuron System to fire in hidden condition. For modeling system that intention recognition through fire effect like Mirror Neuron System, we calculate depth information using stereo image from a stereo camera and reconstruct three dimension data. Movement direction of object is estimated by optical flow with three-dimensional image data created by three dimension reconstruction. For three dimension reconstruction that enables tracing occluded part, first, picture data was get by stereo camera. Result of optical flow is made be robust to noise by the kalman filter estimation algorithm. Image data is saved as history from reconstructed three dimension image through motion tracking of object. When whole or some part of object is disappeared form stereo camera by other objects, it is restored to bring image date form history of saved past image and track motion of object.

Image-Based Ego-Motion Detect of the Unmanned Helicopter using Adaptive weighting (적응형 가중치를 사용한 영상기반 무인 헬리콥터의 Ego-Motion)

  • Chon, Jea-Choon;Chae, Hee-Sung;Shin, Chang-Wan;Kim, Hyong-Suk
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.653-655
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    • 1999
  • 카메라 영상을 통하여 무인 헬리콥터 동작을 추정하기 위해 적응형 가중치를 사용한 새로운 Ego-Motion을 검출 기법을 제안하였다. 무인 헬리콥터 동적 특성은 비선형이며, 심한 진동 발생으로 영상 번짐(blur) 현상이 나타나기 때문에 상관 값만을 고려한 정합 방법으로는 빈번히 오차가 발생한다. 본 논문에서는 가속도, 각 가속도 및 제어입력 값에 의한 위치 추정 값과 상관 값 및 에지 강도를 가중치에 의해 융합하여 정확한 Ego-Motion을 계산할 수 있는 기법을 제안하였다. 또한 무인 헬리콥터의 가속도, 각 가속도, 상하 속도에 따라서 영상의 번짐 정도가 달라 이들 같이 크면 위치오차에 가중을 크게 주고, 작으면 상관 값에 가중치를 적게 주는 적응형 가중치 결정 알고리즘을 적용하였다. 제안한 적응형 가중치 기법을 무인 헬리콥터에 실험한 결과 카메라에 포착된 영상에 의해 무인헬기의 동작을 정확히 추정 할 수 있었다.

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