• 제목/요약/키워드: vision-based method

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PCI비젼 시스템 개발 (Development of PCI Vision System)

  • 김정훈;전재욱;변종은
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 D
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    • pp.2868-2870
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    • 2000
  • Vision systems need to have high speed transfer methods for transferring large data. After PC accepts PCL, PCI becomes a more effective method for data translation. PCI substitutes previous ISA. This paper proposes an architecture of vision system and window driver based on PCI.

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A Video Traffic Flow Detection System Based on Machine Vision

  • Wang, Xin-Xin;Zhao, Xiao-Ming;Shen, Yu
    • Journal of Information Processing Systems
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    • 제15권5호
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    • pp.1218-1230
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    • 2019
  • This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

Classification of Objects using CNN-Based Vision and Lidar Fusion in Autonomous Vehicle Environment

  • G.komali ;A.Sri Nagesh
    • International Journal of Computer Science & Network Security
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    • 제23권11호
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    • pp.67-72
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    • 2023
  • In the past decade, Autonomous Vehicle Systems (AVS) have advanced at an exponential rate, particularly due to improvements in artificial intelligence, which have had a significant impact on social as well as road safety and the future of transportation systems. The fusion of light detection and ranging (LiDAR) and camera data in real-time is known to be a crucial process in many applications, such as in autonomous driving, industrial automation and robotics. Especially in the case of autonomous vehicles, the efficient fusion of data from these two types of sensors is important to enabling the depth of objects as well as the classification of objects at short and long distances. This paper presents classification of objects using CNN based vision and Light Detection and Ranging (LIDAR) fusion in autonomous vehicles in the environment. This method is based on convolutional neural network (CNN) and image up sampling theory. By creating a point cloud of LIDAR data up sampling and converting into pixel-level depth information, depth information is connected with Red Green Blue data and fed into a deep CNN. The proposed method can obtain informative feature representation for object classification in autonomous vehicle environment using the integrated vision and LIDAR data. This method is adopted to guarantee both object classification accuracy and minimal loss. Experimental results show the effectiveness and efficiency of presented approach for objects classification.

Foveated Contrast Sensitivity를 이용한 인지품질 기반 비디오 코딩 (Perceptual Quality-based Video Coding with Foveated Contrast Sensitivity)

  • 유지우;심동규
    • 방송공학회논문지
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    • 제19권4호
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    • pp.468-477
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    • 2014
  • 본 논문은 FCS(foveated contrast sensitivity)를 이용한 인지품질 기반 비디오 코딩 방법을 제안한다. CS(contrast sensitivity)를 이용한 기존의 인지품질 기반 비디오 코딩 방법은 공간주파수에 따라 시각적 인지능력이 달라지는 인간시각체계(HVS, human visual system)의 특징을 이용하여 비디오 압축 시 인지품질의 손상을 최소화하며, FM(foveated masking)을 이용한 방법에서는 HVS의 중심시(central vision) 와 주변시(peripheral vision)의 차를 이용한다. 본 연구에서는, 정신물리학 실험을 통하여 기존의 DCT(discrete cosine transform)기반 JND(Just-noticeable difference) 모델과 FM이 서로 의존성을 갖고 동시에 고려된 새로운 FCS 모델을 제안하였고, 이를 HM10.0 부호화기에 적용하여 인지품질기반 부호화를 수행하였다. 제안된 방법으로 부호화된 영상은 인지품질 관점에서 동일한 화질을 유지하면서 평균 10%의 비트율 감소를 보였다.

Vision Based Map-Building Using Singular Value Decomposition Method for a Mobile Robot in Uncertain Environment

  • Park, Kwang-Ho;Kim, Hyung-O;Kee, Chang-Doo;Na, Seung-Yu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.101.1-101
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    • 2001
  • This paper describes a grid mapping for a vision based mobile robot in uncertain indoor environment. The map building is a prerequisite for navigation of a mobile robot and the problem of feature correspondence across two images is well known to be of crucial Importance for vision-based mapping We use a stereo matching algorithm obtained by singular value decomposition of an appropriate correspondence strength matrix. This new correspondence strength means a correlation weight for some local measurements to quantify similarity between features. The visual range data from the reconstructed disparity image form an occupancy grid representation. The occupancy map is a grid-based map in which each cell has some value indicating the probability at that location ...

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Vision-Based Finger Action Recognition by Angle Detection and Contour Analysis

  • Lee, Dae-Ho;Lee, Seung-Gwan
    • ETRI Journal
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    • 제33권3호
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    • pp.415-422
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    • 2011
  • In this paper, we present a novel vision-based method of recognizing finger actions for use in electronic appliance interfaces. Human skin is first detected by color and consecutive motion information. Then, fingertips are detected by a novel scale-invariant angle detection based on a variable k-cosine. Fingertip tracking is implemented by detected region-based tracking. By analyzing the contour of the tracked fingertip, fingertip parameters, such as position, thickness, and direction, are calculated. Finger actions, such as moving, clicking, and pointing, are recognized by analyzing these fingertip parameters. Experimental results show that the proposed angle detection can correctly detect fingertips, and that the recognized actions can be used for the interface with electronic appliances.

F-Hessian SIFT기반의 철도건널목 영상 감시 시스템 (F-Hessian SIFT-Based Railroad Level-Crossing Vision System)

  • 임형섭;윤학선;김철환;유등렬;조황;이기서
    • 한국전자통신학회논문지
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    • 제5권2호
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    • pp.138-144
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    • 2010
  • 철도건널목에서 SIFT 기반의 알고리즘을 사용한 영상 안전감시 시스템을 구축하고 실험을 수행하여 실제 상황에의 적용가능성을 판별하고 테스트하였다. 이를 위해 영상 획득 이후의 관심 지역과 관심 영역 구분, 특징점의 추출에 따른 데이터 매칭을 단계적으로 진행하였다. 또한 실시간 상황에서 동작이 가능하도록 헤시안 방법을 사용한 특징점 추출 방법을 사용한 SIFT와 다른 알고리즘과의 성능을 시험하였다.

3 차원 곡면 데이터 획득을 위한 멀티 레이져 비젼 시스템 개발 (Development of Multi-Laser Vision System For 3D Surface Scanning)

  • 이정환;권기연;이현철;도영칠;최두진;박진형;김대경;박영준
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.768-772
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    • 2008
  • Various scanning systems have been studied in many industrial areas to acquire a range data or to reconstruct an explicit 3D model. Currently optical technology has been used widely by virtue of noncontactness and high-accuracy. In this paper, we describe a 3D laser scanning system developped to reconstruct the 3D surface of a large-scale object such as a curved-plate of ship-hull. Our scanning system comprises of 4ch-parallel laser vision modules using a triangulation technique. For multi laser vision, calibration method based on least square technique is applied. In global scanning, an effective method without solving difficulty of matching problem among the scanning results of each camera is presented. Also minimal image processing algorithm and robot-based calibration technique are applied. A prototype had been implemented for testing.

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무인수상선의 단일 카메라를 이용한 VFH+ 기반 장애물 회피 기법 (VFH+ based Obstacle Avoidance using Monocular Vision of Unmanned Surface Vehicle)

  • 김태진;최진우;이영준;최현택
    • 한국해양공학회지
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    • 제30권5호
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    • pp.426-430
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    • 2016
  • Recently, many unmanned surface vehicles (USVs) have been developed and researched for various fields such as the military, environment, and robotics. In order to perform purpose specific tasks, common autonomous navigation technologies are needed. Obstacle avoidance is important for safe autonomous navigation. This paper describes a vector field histogram+ (VFH+) based obstacle avoidance method that uses the monocular vision of an unmanned surface vehicle. After creating a polar histogram using VFH+, an open space without the histogram is selected in the moving direction. Instead of distance sensor data, monocular vision data are used for make the polar histogram, which includes obstacle information. An object on the water is recognized as an obstacle because this method is for USV. The results of a simulation with sea images showed that we can verify a change in the moving direction according to the position of objects.

머리의 자세를 추적하기 위한 효율적인 카메라 보정 방법에 관한 연구 (An Efficient Camera Calibration Method for Head Pose Tracking)

  • 박경수;임창주;이경태
    • 대한인간공학회지
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    • 제19권1호
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    • pp.77-90
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    • 2000
  • The aim of this study is to develop and evaluate an efficient camera calibration method for vision-based head tracking. Tracking head movements is important in the design of an eye-controlled human/computer interface. A vision-based head tracking system was proposed to allow the user's head movements in the design of the eye-controlled human/computer interface. We proposed an efficient camera calibration method to track the 3D position and orientation of the user's head accurately. We also evaluated the performance of the proposed method. The experimental error analysis results showed that the proposed method can provide more accurate and stable pose (i.e. position and orientation) of the camera than the conventional direct linear transformation method which has been used in camera calibration. The results of this study can be applied to the tracking head movements related to the eye-controlled human/computer interface and the virtual reality technology.

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