• Proceedings of the KAIS Fall Conference
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• 2012.05b
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• pp.812-816
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• 2012

본 논문은 산사태 감지 및 붕괴예측을 위한 현장에 USN(Ubiquitous Sensor Network)을 적용한 실시간 모니터링 시스템 모델을 개발하였다. 이 시스템의 성능을 검증하기 위해 USN기반의 상시모니터링시스템모델을 제작하고 실험적 평가를 수행하였다. 성능평가는 지표변위 센서모듈 동작특성 실험적 평가, USN은 Data 수집 전송 효율성 실험적 평가, 개발한 상시감시모니터링 프로그램 동작성능 실험적 평가 등을 수행하였다. 성능평가 결과 지표변위 측정센서모듈은 변위각도에 일치성을 확인하고, USN은 지표변위 센서모듈로부터 측정된 Data를 상시모니터링시스템에 오류 없이 전송되는지를 확인하였으며, 개발한 상시모니터링 프로그램 동작기능은 실시간 모니터링 그래프, 임계동작 알고리즘, 위험성 통보 문자서비스(SMS)기능, 알람서비스기능, 현장 감시카메라 등 동작기능의 우수성을 실험으로 증명하였다. 따라서 본 연구에서 개발된 산사태 감지 예측을 위한 USN기반 실시간 모니터링 시스템 모델은 산사태위험성노출 지역에 원격 실시간 모니터링 시스템으로 널리 사용될 것으로 사료된다.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.225-236
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• 2010

This study proposes a method for the recognition of emergency situation according to the bimodal information of camera image sensor and gravity sensor. This method can recognize emergency condition by mutual cooperation and compensation between sensors even when one of the sensors malfunction, the user does not carry gravity sensor, or in the place like bathroom where it is hard to acquire camera images. This paper implemented HMM(Hidden Markov Model) based learning and recognition algorithm to recognize actions such as walking, sitting on floor, sitting at sofa, lying and fainting motions. Recognition rate was enhanced when image feature vectors and gravity feature vectors are combined in learning and recognition process. Also, this method maintains high recognition rate by detecting moving object through adaptive background model even in various illumination changes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.861-864
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• 2007

본 논문에서는 카메라-투영 시스템에서 비전에 기반을 둔 팔동작 인식을 위한 새로운 알고리즘을 제안하고 있다. 제안된 인식방법은 정적인 팔동작 분류를 위하여 푸리에 변환을 사용하였다. 팔 분할은 개선된 배경 제거 방법을 사용하였다. 대부분의 인식방법들이 같은 피검자에 의해 학습과 실험이 이루어지고 상호작용 이전에 학습단계가 필요하다. 그러나 학습되지 않은 다양한 상황에 대해서도 상호작용을 위해 동작 인식이 요구된다. 그러므로 본 논문에서는 인식 작업 중에 검출된 불완전한 동작들을 정정하여 적용하였다. 그 결과 사용자와 독립되게 동작을 인식함으로써 새로운 사용자에게 신속하게 온라인 적용이 가능하였다.

• Journal of Korea Game Society
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• v.21 no.5
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• pp.105-114
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• 2021

In this study, we analyzed the motion animation of game characters, which is a visual part of the game elements for 'Hit Impact'. The game selected for analysis focused on the movements of the characters in the arcade game , which is thought to have a weak 'Hit Impact' and looked for the cause. We also analyzed the differences in the motion of the characters in the home transplant version of , which is considered to have improved 'Hit Impact', compared to the arcade version. As a result of the analysis, it was found that the reason for the weak 'Hit Impact' in the arcade version was mainly due to the wrong timing and judgment of hitting and hitting movements, and at the same time, supplemented physical reactions and stun, camera directing, and hitting effects could have a significant impact on improving 'Hit Impact'.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.780-785
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• 2012

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around the world. Generally, wind turbine systems are designed to be operated for twenty years long, Therefore, various faults in the wind turbine system inevitably occur during their long term period of operation. Especially, rotor shaft, gear-box and generator are installed inside of nacelle, furthermore, some cooling systems for normal operation of these devices are also required. If these cooing systems have failed in their operation, it is impossible for the entire system to be operated normally. In this work, IR(Infra Red) camera based fault detection system for the preventive detection of various cooling systems faults is proposed. To verify the applicability of the proposed system, physical implementation is embodied and various experiments are carried out.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.374-376
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• 2018

In this study, we developed a mobile home robot using a face recognition method using a camera attached to a raspberry pie. It receives the real time image through the camera attached to the raspberry pie, recognizes the face of the person, and distinguishes the operation of the smart cool air temperature device according to the result. It is expected that the robot will be able to increase the energy utilization efficiency by allowing the robot to operate in cold and hot winds only where there is no human being, instead of operating the hot and cold air conditioner.

• 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.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.124-129
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• 2006

음악은 소리를 즐긴다는 뜻을 담고 있다. 감상자에게 단순한 청각적 자극을 넘어 즐거움을 주기 위해선 음악적인 경험이 뒷받침되어야 한다. 가상 현실을 이용한 사용자와 시스템 간의 상호작용을 음악 경험 제공에 접목하려는 시도는, 새로운 경험을 통해 일반인들이 보다 쉽게 음악을 접하고 체험함으로써 음악을 통해 즐거움을 얻을 수 있도록 도움을 주는 데에 그 목적이 있다. 가상 오케스트라를 구현하고 지휘 동작을 재현하는 것은 이러한 가능성을 극대화하는 연구이다. 본 논문에서는 가상 오케스트라를 구현하기 위해 필수적인 중간 단계로, 사용자의 지휘 동작을 감지하여 연주의 박자(속도)를 제어하는 지휘 시뮬레이션 시스템을 제시한다. 실제의 지휘 동작을 분석하고, 동작의 변화를 인식하기 위하여 가속도 센서를 이용, 공간상에서 지휘봉의 움직임을 가속도 정보로 수집하여 이에 상응하는 박자의 제어를 구현한다. 사용자의 박자 명시에 따라 변화하는 상하 방향의 가속도를 센서를 통해 전압 신호로 입력 받고, DSP 의 A/D conversion 모듈에서 디지털 신호로 변환, 일정 수준 이상의 신호를 박자 정보로 직렬통신을 통해 컴퓨터에 전달한다. 컴퓨터에서는 Max/MSP를 이용하여 각 박자 사이의 시간 간격을 측정하고 상응하는 MIDI 음악을 재생하는 방식으로 시스템이 구현된다. 기존 연구에서 사용된 CCD 카메라에 의한 Motion Tracking 을 보완하여 동작의 크기에 따라 음량을 조절한다. 본 논문에서 제시되는 시스템은 지휘 동작에서 가장 특징적으로 나타나는 상하 방향의 급격한 가속도 변화를 직접 입력 받기 때문에 기존 시스템에 비해 지휘 동작의 인식 성공률을 높일 수 있으며, 화상 처리 및 계산에 의한 지연을 최소화할 수 있다. 또한, 장치의 규모를 소형화하여 보다 지휘봉의 형태에 가까운 인터페이스를 제공하며, 적합한 응용 콘텐츠를 접목할 경우 게임 컨트롤러로의 발전 가능성이 있다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.62-78
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• 2002

In this paper, we describe a system that can interact with agents in the virtual space incorporated in the system. This system is constructed by an analysis system for analyzing human gesture and an interact system for interacting with agents in the virtual space using analyzed information. An implemented analysis system for analyzing gesture extracts a head and hands region after taking image sequence of an operator's continuous behavior using CCD cameras. In interact system, we construct the virtual space that exist an avatar which incarnating operator himself, an autonomous object (like a Puppy), and non-autonomous objects which are table, door, window and object. Recognized gesture is transmitted to the avatar in the virtual space, then transit to next state based on state transition diagram. State transition diagram is represented in a graph in which each state represented as node and connect with link. In the virtual space, the agent link an avatar can open and close a window and a door, grab or move an object like a ball, order a puppy to do and respond to the Puppy's behavior as does the puppy.

• Smart Media Journal
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• v.1 no.2
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• pp.12-22
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• 2012

Today we are witnessing an increasingly widespread use of cameras in our lives for video surveillance, robot vision, and mobile phones. This has led to a renewed interest in computer vision in general and an on-going boom in human activity recognition in particular. Although not particularly fancy per se, human gait is inarguably the most common and frequent action. Early on this decade there has been a passing interest in human gait recognition, but it soon declined before we came up with a systematic analysis and understanding of walking motion. This paper presents a set of DBN-based models for the analysis of human gait in sequence of increasing complexity and modeling power. The discussion centers around HMM-based statistical methods capable of modeling the variability and incompleteness of input video signals. Finally a novel idea of extending the discrete state Markov chain with a continuous density function is proposed in order to better characterize the gait direction. The proposed modeling framework allows us to recognize pedestrian up to 91.67% and to elegantly decode out two independent gait components of direction and posture through a sequence of experiments.