• 제목/요약/키워드: visual tracking algorithm

검색결과 131건 처리시간 0.027초

한국 e-CALLISTO 관측소 자동 관측 시스템 개발 (DEVELOPMENT OF AN AUTOMATIC OBSERVATION SYSTEM FOR KOREAN e-CALLISTO STATION)

  • 박종엽;최성환;봉수찬;권용준;백지혜;장비호;조경석;문용재
    • 천문학논총
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    • 제30권3호
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    • pp.811-819
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    • 2015
  • The e-CALLISTO is a network of CALLISTO (Compact Astronomical Low-frequency, Low-cost Instrument for Spectroscopy in Transportable Observatories) spectrometers which detect solar radio bursts 24 hours a day in frequency range 45-870 MHz. The number of channels per spectrum is 200 and the time resolution of whole spectrum is 0.25 second. The Korean e-CALLISTO station was developed by Korea Astronomy and Space Science Institute (KASI) collaborating with Swiss Federal Institute of Technology Zurich (ETH Zurich) since 2007. In this paper, we report replacement of the tracking mount and development of the control program using Visual C++/MFC. The program can make the tracking mount track the Sun and schedule CALLISTO to start and to finish its observation automatically using the Solar Position Algorithm (SPA). Daily tracking errors (RMSE) are 0.0028 degree in azimuthal axis and 0.0019 degree in elevational axis between 2014 January and 2015 July. We expect that the program can save time and labor to make the observations of solar activity for space weather monitoring, and improve CALLISTO data quality due to the stable and precise tracking methods.

HMM을 이용한 알파벳 제스처 인식 (Alphabetical Gesture Recognition using HMM)

  • 윤호섭;소정;민병우
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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    • pp.384-386
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    • 1998
  • The use of hand gesture provides an attractive alternative to cumbersome interface devices for human-computer interaction(HCI). Many methods hand gesture recognition using visual analysis have been proposed such as syntactical analysis, neural network(NN), Hidden Markov Model(HMM) and so on. In our research, a HMMs is proposed for alphabetical hand gesture recognition. In the preprocessing stage, the proposed approach consists of three different procedures for hand localization, hand tracking and gesture spotting. The hand location procedure detects the candidated regions on the basis of skin-color and motion in an image by using a color histogram matching and time-varying edge difference techniques. The hand tracking algorithm finds the centroid of a moving hand region, connect those centroids, and thus, produces a trajectory. The spotting a feature database, the proposed approach use the mesh feature code for codebook of HMM. In our experiments, 1300 alphabetical and 1300 untrained gestures are used for training and testing, respectively. Those experimental results demonstrate that the proposed approach yields a higher and satisfying recognition rate for the images with different sizes, shapes and skew angles.

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카메라 영상기반 전방향 이동 로봇의 제어 (Control of an Omni-directional Mobile Robot Based on Camera Image)

  • 김봉규;류정래
    • 한국지능시스템학회논문지
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    • 제24권1호
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    • pp.84-89
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    • 2014
  • 본 논문에서는 카메라를 탑재한 전방향 이동 로봇에서의 표적 추종을 위한 영상기반 시각 서보 제어를 다룬다. 기존 연구에서는 카메라 영상에서 추출한 표적의 영상 좌표로부터 표적 추종을 위한 바퀴의 회전 각속도를 구하기 위하여 카메라의 수학적 모델과 이동 로봇의 기구학 특성으로부터 구한 수학적 영상 자코비안을 널리 활용하였다. 본 논문에서는 표적의 영상 좌표 정보를 이용한 단순한 규칙기반 제어 방식과 영상에 포착된 표적의 크기 정보를 조합하여 바퀴의 회전 각속도를 생성하는 새로운 방식을 제안한다. 카메라 영상을 몇 개의 영역으로 분할하고, 표적이 포함된 영역에 따라 미리 정의한 규칙을 적용하는데, 복잡한 수학적 표현을 사용하지 않으면서도 비교적 적은 수의 규칙을 사용하므로 구현이 용이한 장점이 있다. 제안된 방식은 실제 시스템으로 구현하여 실험하고, 전체 실험 시스템에 대한 설명과 함께 실험 결과를 제시하여 제안하는 방식의 타당성을 입증한다.

수중용 선체외판 길함 검사용 장치 개발 (An Underwater Inspection System to Detect Hull Defects of a Ship)

  • 김영진;조영준;이강원;손웅희
    • 한국해양공학회:학술대회논문집
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    • 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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    • pp.281-284
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    • 2006
  • After building a ship in a shipyard, there are so many repeated inspection of welding seam defects and painting status before delivering to the ship's owner. An inspection on the bottom part of a ship in commercial service should be done in every two years for the purpose of safety and for the prevention of ship speed deterioration. conventional welding seam inspection systems are rely on the visual inspection by human or the ultrasonic inspection for the selective part of a ship. This paper suggests a remote controlled inspection system for the examination of large ships or steel structures. The proposed system moves in contact with the ship under inspection and have a CCD camera to provide visual-guidance information to a remotely located human worker. Additionally this system utilizes a weld line tracking algorithm for an optimal position control. We verified the effectiveness of the inspection system by experimental data.

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감시 영상에서의 장면 분석을 통한 이상행위 검출 (Detection of Abnormal Behavior by Scene Analysis in Surveillance Video)

  • 배건태;어영정;곽수영;변혜란
    • 한국통신학회논문지
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    • 제36권12C호
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    • pp.744-752
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    • 2011
  • 지능형 감시 분야에서 이상행위를 검출하는 것은 오랫동안 연구되어온 주제로 다양한 방법들이 제안되어 왔다. 그러나 많은 연구가 움직이는 객체의 개별적인 추적이 가능하다는 것을 전제로 하여 찾은 가려짐이 발생하는 실생활에 적용하는데 한계가 있다. 본 논문에서는 객체 추적이 어려운 복잡한 환경에서 장면의 주된 움직임을 분석하여 비정상적인 행위를 검출하는 방법을 제안한다. 먼저, 입력영상에서 움직임 정보를 추출하여 Visual Word와 Visual Document를 생성하고, 문서 분석 기법 중 하나인 LDA(Latent Dirichlet Allocation 알고리즘을 이용하여 장면의 주요한 움직임 정보j위치, 크기, 방향, 분포)를 추출한다. 이렇게 분석된 장면의 주요한 움직임과 입력영상에서 발생한 움직임과의 유사도를 분석하여 주요한 움직임에서 벗어나는 움직임을 비정상적인 움직임으로 간주하고 이를 이상행위로 검출하는 방법을 제안한다.

YOLOv8 알고리즘 기반의 주행 가능한 도로 영역 인식과 실시간 추적 기법에 관한 연구 (Research on Drivable Road Area Recognition and Real-Time Tracking Techniques Based on YOLOv8 Algorithm)

  • 서정희
    • 한국전자통신학회논문지
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    • 제19권3호
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    • pp.563-570
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    • 2024
  • 본 논문은 운전자의 운행 보조 역할로 주행 가능한 차선 영역을 인식하고 추적하는 방법을 제안한다. 주요 주제는 차량 내부의 앞 유리 중앙에 설치된 카메라를 통해 실시간으로 획득한 영상을 기반으로 컴퓨터 비전과 딥 러닝 기술을 활용하여 주행 가능한 도로 영역을 예측하는 심층 기반 네트워크를 설계한다. 본 연구는 YOLOv8 알고리즘을 이용하여 카메라에서 직접 획득한 데이터로 훈련한 새로운 모델을 개발하는 것을 목표한다. 실제 도로에서 자신의 차량의 정확한 위치를 실제 영상과 일치하게 시각화하여 주행 가능한 차선 영역을 표시 및 추적함으로써 운전자 운행의 보조하는 역할을 기대한다. 실험 결과, 대부분 주행 가능한 도로 영역의 추적이 가능했으나 밤에 비가 심하게 오는 경우와 같은 악천후에서 차선이 정확하게 인식되지 않는 경우가 발생하여 이를 해결하기 위한 모델의 성능 개선이 필요하다.

Terrain Geometry from Monocular Image Sequences

  • McKenzie, Alexander;Vendrovsky, Eugene;Noh, Jun-Yong
    • Journal of Computing Science and Engineering
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    • 제2권1호
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    • pp.98-108
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    • 2008
  • Terrain reconstruction from images is an ill-posed, yet commonly desired Structure from Motion task when compositing visual effects into live-action photography. These surfaces are required for choreography of a scene, casting physically accurate shadows of CG elements, and occlusions. We present a novel framework for generating the geometry of landscapes from extremely noisy point cloud datasets obtained via limited resolution techniques, particularly optical flow based vision algorithms applied to live-action video plates. Our contribution is a new statistical approach to remove erroneous tracks ('outliers') by employing a unique combination of well established techniques-including Gaussian Mixture Models (GMMs) for robust parameter estimation and Radial Basis Functions (REFs) for scattered data interpolation-to exploit the natural constraints of this problem. Our algorithm offsets the tremendously laborious task of modeling these landscapes by hand, automatically generating a visually consistent, camera position dependent, thin-shell surface mesh within seconds for a typical tracking shot.

Affine-Invariant Image normalization for Log-Polar Images using Momentums

  • Son, Young-Ho;You, Bum-Jae;Oh, Sang-Rok;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1140-1145
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    • 2003
  • Image normalization is one of the important areas in pattern recognition. Also, log-polar images are useful in the sense that their image data size is reduced dramatically comparing with conventional images and it is possible to develop faster pattern recognition algorithms. Especially, the log-polar image is very similar with the structure of human eyes. However, there are almost no researches on pattern recognition using the log-polar images while a number of researches on visual tracking have been executed. We propose an image normalization technique of log-polar images using momentums applicable for affine-invariant pattern recognition. We handle basic distortions of an image including translation, rotation, scaling, and skew of a log-polar image. The algorithm is experimented in a PC-based real-time vision system successfully.

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Environment Modeling for Autonomous Welding Robotus

  • Kim, Min-Y.;Cho, Hyung-Suk;Kim, Jae-Hoon
    • Transactions on Control, Automation and Systems Engineering
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    • 제3권2호
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    • pp.124-132
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    • 2001
  • Autonomous of welding process in shipyard is ultimately necessary., since welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding robot that can navigate autonomously within the enclosure needs to be developed. To achieve the welding ra나, the robotic welding systems needs a sensor system for the recognition of the working environments and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with work environmental map. At the same time a strategy for environment recognition for welding mobile robot is proposed in order to recognize the work environment efficiently. The design of the sensor system, the algorithm for sensing the structured environment, and the recognition strategy and tactics for sensing the work environment are described and dis-cussed in detail.

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Integrated Approach of Multiple Face Detection for Video Surveillance

  • Kim, Tae-Kyun;Lee, Sung-Uk;Lee, Jong-Ha;Kee, Seok-Cheol;Kim, Sang-Ryong
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.1960-1963
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    • 2003
  • For applications such as video surveillance and human computer interface, we propose an efficiently integrated method to detect and track faces. Various visual cues are combined to the algorithm: motion, skin color, global appearance and facial pattern detection. The ICA (Independent Component Analysis)-SVM (Support Vector Machine based pattern detection is performed on the candidate region extracted by motion, color and global appearance information. Simultaneous execution of detection and short-term tracking also increases the rate and accuracy of detection. Experimental results show that our detection rate is 91% with very few false alarms running at about 4 frames per second for 640 by 480 pixel images on a Pentium IV 1㎓.

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