• 제목/요약/키워드: motion detection

검색결과 1,060건 처리시간 0.023초

지역적 가중치 거리맵을 이용한 3차원 영상 정합 (Three-Dimensional Image Registration using a Locally Weighted-3D Distance Map)

  • 이호;홍헬렌;신영길
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제31권7호
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    • pp.939-948
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    • 2004
  • 본 논문에서는 동일 환자에 대해 시간차를 두고 촬영한 뇌 CT-CT 혈관조영영상간 움직임을 보정하기 위한 강인하고 고속의 정합방법을 제안한다. 먼저, 두 영상에서 3차원 경계검출 기법을 이용하여 특징점을 추출하고, 기준영상에서는 이를 지역적 가중치 3차원 거리맵으로 변환한다. 부유영상을 기준영상으로 강체변환하면서 두 경계간의 상관관계가 최대인 위치를 탐색한다. 이 때, 최대위치가 더 이상 변화하지 않고 일정 이상 반복되면 해당위치를 최적위치로 하여 부유영상을 최적위치로 변환시켜 두 영상을 정합한다. 실험을 위하여 인공영상을 사용하여 정화성과 강인성을 평가하였고, 육안평가를 위하여 뇌 CT-CT 혈관조영영상을 사용하였다. 본 제안방법은 지역적 가중치 3차원 거리맵을 이용함으로써 적은 샘플링 개수에도 국부최대인 위치에 수렴하지 않고 최적위치로 강인하면서 고속으로 영상이 정합되었다

웨이브릿 임계치 잡음제거에 의한 파형의 변곡점 검출 (Detection of Inflection Point of Waveform by Wavelet Threshold Denoising)

  • 김태수
    • 한국정보통신학회논문지
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    • 제13권10호
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    • pp.2205-2210
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    • 2009
  • 본 논문에서 제안하는 잡음제거 방법은 hard 임계치 방법의 문제점을 개선한 제로점의 탄젠트 곡선 보간에 의한 잡음제거 기술이다. 자연계에서 관측되는 대기 전기변동량과 같은 신호의 시간적 변동량이나 가상현실을 이용하여 추출한사람의 빠른 움직임의 동작 곡선 등은 실제로 복잡하다. 따라서 이러한 신호의 관측파형에 대하여 변곡점에 대한 특징을 정확히 결정하는 것이 매우 중요하다. 특히 자연계의 측정 신호는 잡음이 포함되어 있어서 잡음을 제거하고 특징을 추출하는 것이 필요하다. 본 논문에서 제안한 새로운 방식에 의하여 잡음을 제거하고 변곡점을 추출하며 종래의 방식인 hard 임계치에 비하여 잡음지수가 5인 경우의 noise II 변곡점 신호에 대하여 SNR이 3.4dB 개선된 결과를 얻을 수 있음을 보였다.

Trend of Technology in Video Surveillance System

  • Song, Jaemin;Park, Arum;Lee, Sae Bom
    • 한국컴퓨터정보학회논문지
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    • 제25권6호
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    • pp.57-64
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    • 2020
  • 영상보안은 카메라, 전송장치, 저장 및 재생장치 등으로 구성되며 범죄예방, 재난 감시 등에 사용되고 있다. 최근 매우 다양한 분야로 파급되고 있으며, 자동으로 사람 및 사물의 특징적인 객체를 인식하거나 추적할 수 있는 지능형 영상보안 시스템으로 발전하고 있다. 본 연구는 홈과 공공부문, 민간부문으로 구분하여 최신 기술을 적용한 영상보안 서비스 사례들을 조사하고 비즈니스 관점에서 어떠한 이점을 가져다주는지 조사·연구하고자 하였다. 본 연구에서 소개한 사례들을 살펴봄으로써 뛰어난 CCTV와의 호환, 여러 개의 영상감시, CCTV 촬영 화면 모션 감지, 자동 분석을 통한 알람 제공 등 영상보안 서비스가 지능적으로 발전하고 있다는 것을 확인할 수 있었다.

Transition-based Data Decoding for Optical Camera Communications Using a Rolling Shutter Camera

  • Kim, Byung Wook;Lee, Ji-Hwan;Jung, Sung-Yoon
    • Current Optics and Photonics
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    • 제2권5호
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    • pp.422-430
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    • 2018
  • Rolling shutter operation of CMOS cameras can be utilized in optical camera communications in order to transmit data from an LED to mobile devices such as smart-phones. From temporally modulated light, a spatial flicker pattern is obtained in the captured image, and this is used for signal recovery. Due to the degradation of rolling shutter images caused by light smear, motion blur, and focus blur, the conventional decoding schemes for rolling shutter cameras based on the pattern width for 'OFF' and 'ON' cannot guarantee robust communications performance for practical uses. Aside from conventional techniques, such as polynomial fitting, histogram equalization can be used for blurry light mitigation, but it requires additional computation abilities resulting in burdens on mobile devices. This paper proposes a transition-based decoding scheme for rolling shutter cameras in order to offer simple and robust data decoding in the presence of image degradation. Based on the designed synchronization pulse and modulated data symbols according to the LED dimming level, the decoding process is conducted by observing the transition patterns of two sequential symbol pulses. For this, the extended symbol pulse caused by consecutive symbol pulses with the same level determines whether the second pulse should be included for the next bit decoding or not. The proposed method simply identifies the transition patterns of sequential symbol pulses other than the pattern width of 'OFF' and 'ON' for data decoding, and thus, it is simpler and more accurate. Experimental results ensured that the transition-based decoding scheme is robust even in the presence of blurry lights in the captured image at various dimming levels

Cow Residual Feed Intake(RFI) monitoring and metabolic abnormality prediction system using wearable device for Milk cow and Beef

  • Chang, Jin-Wook;Kwak, Ho-Young
    • 한국컴퓨터정보학회논문지
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    • 제26권10호
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    • pp.139-145
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    • 2021
  • 본 논문에서는 소의 사료 취식량(Feed Intake), 반추(Rumination), 발정기(In Heat) 모니터링 기술을 이용하여, RFI(Residual Feed Intake) 모니터링 및 신진대상 이상을 예측하는 웨어러블 디바이스 및 PC용 웹과 스마트폰 어플리케이션을 이용한 모니터링 시스템을 설계하고 구현하였다. 본 시스템의 개발로 농장주는 경제적 효율성의 증가가 기대된다. 사료 섭취량을 분석하면, 소의 체중에 근거한 추천 사료량과 소가 섭취하는 사료량과의 차이를 확인할 수 있으며, Metabolic disorder(신진대사 이상)에 대한 조기 발견이 가능할 것으로 예상된다. 본 논문의 결과물을 사용하는 농장주는 가장 효율적인 성과를 나타내는 소를 구별할 수 있으며, 소의 표피(목)에 부착하는 웨어러블 장치로부터 입력되는 6축 모션 센서 신호와 웨어러블 장치에 부착된 마이크를 통해 입력되는 소의 목넘김 소리를 통해서 소의 반추와 사료섭취량을 측정할 수 있다. 향후에는 심박, 호흡 등의 추가적인 생체신호를 측정할 수 있도록 개선 작업을 진행할 예정이다.

Using multiple sequence alignment to extract daily activity routines of the elderly living alone

  • Lee, Bogyeong;Lee, Hyun-Soo;Park, Moonseo;Ahn, Changbum Ryan;Choi, Nakjung;Kim, Toseung
    • Advances in Computational Design
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    • 제4권2호
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    • pp.73-90
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    • 2019
  • The growth in the number of single-member households is a critical issue worldwide, especially among the elderly. For those living alone, who may be unaware of their health status or routines that could improve their health, a continuous healthcare monitoring system could provide valuable feedback. Assessing the performance adequacy of activities of daily living (ADL) can serve as a measure of an individual's health status; previous research has focused on determining a person's daily activities and extracting the most frequently performed behavioral patterns using camera recordings or wearable sensing techniques. However, existing methods used to extract common patterns of an occupant's activities in the home fail to address the spatio-temporal dimensions of human activities simultaneously. Though multiple sequence alignment (MSA) offers some advantages - such as inherent containment of the spatio-temporal data in sequence format, and rapid identification of hidden patterns - MSA has rarely been used to extract in-home ADL routines. This research proposes a method to extract a household occupant's ADL routines from a cumulative spatio-temporal data log of occupancy collected using a non-intrusive method (i.e., a tomographic motion detection system). The findings from an occupant's 28-day spatio-temporal activity log demonstrate the capacity of the proposed approach to identify routine patterns of an occupant's daily activities and to reveal the order, duration, and frequency of routine activities. Routine ADL patterns identified from the proposed approach are expected to provide a basis for detecting/evaluating abrupt or gradual changes of an occupant's ADL patterns that result from a physical or mental disorder, and can offer valuable information for home automation applications by enabling the prediction of ADL patterns.

UAS 및 지상 LiDAR 융합기반 건축물의 3D 재현 (3D Reconstruction of Structure Fusion-Based on UAS and Terrestrial LiDAR)

  • 한승희;강준오;오성종;이용창
    • 도시과학
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    • 제7권2호
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    • pp.53-60
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    • 2018
  • Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.

A CPU-GPU Hybrid System of Environment Perception and 3D Terrain Reconstruction for Unmanned Ground Vehicle

  • Song, Wei;Zou, Shuanghui;Tian, Yifei;Sun, Su;Fong, Simon;Cho, Kyungeun;Qiu, Lvyang
    • Journal of Information Processing Systems
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    • 제14권6호
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    • pp.1445-1456
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    • 2018
  • Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

청소년기 야구 선수의 박리성 골연골염에서 주관절 외측 구획 성장판의 조기 폐쇄 (Early Lateral Compartment Physeal Closure of the Elbow in Osteochondritis Dissecans of the Adolescent Baseball Players)

  • 구정회;조형래;박기봉;이완석
    • 대한스포츠의학회지
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    • 제36권4호
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    • pp.180-188
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    • 2018
  • Purpose: The purpose of this study is to identify bilateral differences of physeal closure of the lateral compartment of the elbow in osteochondritis dissecans (OCD) and related factors with premature physeal closure. Methods: Initial radiographs of the bilateral elbows in 40 baseball players with OCD (group I) were reviewed for the status of physeal closure of the lateral compartment; capitellum, radial head, lateral epicondyle. Forty baseball players with medial epicondylar apophysitis (group II) were enrolled as a control. Relative status of physeal closure of dominant elbow was defined as early, same, and delayed. Bilateral differences of the status of physeal closure were analyzed between groups, and according to the radiographic stages, extent of the lesions and demographic factors in group I. Results: Significant early physeal closures of dominant elbows were identified in group I in capitellum (group I, 55%; group II, 3%), radial head (group I, 53%; group II, 3%), and lateral epicondyle (group I 37%; group II, 5%). In group I, advanced stage and extended lesion showed early lateral compartment physeal closure especially in capitellum and radial head, and players with longer career length and limitation of motion showed early closure. Conclusion: Over the half of the adolescent baseball players with OCD demonstrated early radiocapitellar physeal closures of dominant elbow in initial presentation. Because premature physeal closure contributes to the development of arthritis without appropriate radiocapitellar remodeling, early detection of OCD is essential for prevention of arthritis and successful conservative management.

SVM 모델 기반 가용성 예측 기능을 가진 야외마루 관리 서비스 구현 및 성능 평가 (Implementation and Performance Evaluation of Pavilion Management Service including Availability Prediction based on SVM Model)

  • 리자얀티 리타;황민태
    • 한국정보통신학회논문지
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    • 제25권6호
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    • pp.766-773
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    • 2021
  • 본 논문은 숲속 야외 마루의 실시간 이용 현황을 제공할 뿐만 아니라 기계학습을 통한 예측 서비스를 제공하는 야외 마루 관리 서비스의 구현 및 성능 평가 결과를 담고있다. 개발한 하드웨어 프로토타입은 모션 감지 센서를 이용해 야외 마루의 점유 여부를 감지한 후 위치 정보, 날짜 및 시간, 온도 및 습도 데이터와 함께 클라우드 기반 데이터베이스로 전달한다. 수집된 야외 마루의 실시간 이용 현황은 이용자들에게 모바일 애플리케이션을 통해 제공된다. 성능 평가 결과 하드웨어 모듈에서부터 모바일 애플리케이션까지 평균 1.9초의 응답 시간을 보여주었으며, 정확도는 99%를 보여주고 있음을 확인하였다. 아울러 수집 데이터에다 기계학습 기반의 SVM(Support Vector Model) 모델을 적용한 야외 마루의 가용성 예측 서비스를 구현하고서 이를 모바일 및 웹 애플리케이션을 통해 제공할 수 있도록 하였다.