• 제목/요약/키워드: Tracking network

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Real-time Zoom Tracking for DM36x-based IP Network Camera

  • Cong, Bui Duy;Seol, Tae In;Chung, Sun-Tae;Kang, HoSeok;Cho, Seongwon
    • 한국멀티미디어학회논문지
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    • 제16권11호
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    • pp.1261-1271
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    • 2013
  • Zoom tracking involves the automatic adjustment of the focus motor in response to the zoom motor movements for the purpose of keeping an object of interest in focus, and is typically achieved by moving the zoom and focus motors in a zoom lens module so as to follow the so-called "trace curve", which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. Thus, one can simply implement zoom tracking by following the most closest trace curve after all the trace curve data are stored in memory. However, this approach is often prohibitive in practical implementation because of its large memory requirement. Many other zoom tracking methods such as GZT, AZT and etc. have been proposed to avoid large memory requirement but with a deteriorated performance. In this paper, we propose a new zoom tracking method called 'Approximate Feedback Zoom Tracking method (AFZT)' on DM36x-based IP network camera, which does not need large memory by approximating nearby trace curves, but generates better zoom tracking accuracy than GZT or AZT by utilizing focus value as feedback information. Experiments through real implementation shows the proposed zoom tracking method improves the tracking performance and works in real-time.

Lightweight high-precision pedestrian tracking algorithm in complex occlusion scenarios

  • Qiang Gao;Zhicheng He;Xu Jia;Yinghong Xie;Xiaowei Han
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권3호
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    • pp.840-860
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    • 2023
  • Aiming at the serious occlusion and slow tracking speed in pedestrian target tracking and recognition in complex scenes, a target tracking method based on improved YOLO v5 combined with Deep SORT is proposed. By merging the attention mechanism ECA-Net with the Neck part of the YOLO v5 network, using the CIoU loss function and the method of CIoU non-maximum value suppression, connecting the Deep SORT model using Shuffle Net V2 as the appearance feature extraction network to achieve lightweight and fast speed tracking and the purpose of improving tracking under occlusion. A large number of experiments show that the improved YOLO v5 increases the average precision by 1.3% compared with other algorithms. The improved tracking model, MOTA reaches 54.3% on the MOT17 pedestrian tracking data, and the tracking accuracy is 3.7% higher than the related algorithms and The model presented in this paper improves the FPS by nearly 5 on the fps indicator.

Analysis on Tracking Schedule and Measurements Characteristics for the Spacecraft on the Phase of Lunar Transfer and Capture

  • Song, Young-Joo;Choi, Su-Jin;Ahn, Sang-Il;Sim, Eun-Sup
    • Journal of Astronomy and Space Sciences
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    • 제31권1호
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    • pp.51-61
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    • 2014
  • In this work, the preliminary analysis on both the tracking schedule and measurements characteristics for the spacecraft on the phase of lunar transfer and capture is performed. To analyze both the tracking schedule and measurements characteristics, lunar transfer and capture phases' optimized trajectories are directly adapted from former research, and eleven ground tracking facilities (three Deep Space Network sties, seven Near Earth Network sites, one Daejeon site) are assumed to support the mission. Under these conceptual mission scenarios, detailed tracking schedules and expected measurement characteristics during critical maneuvers (Trans Lunar Injection, Lunar Orbit Insertion and Apoapsis Adjustment Maneuver), especially for the Deajeon station, are successfully analyzed. The orders of predicted measurements' variances during lunar capture phase according to critical maneuvers are found to be within the order of mm/s for the range and micro-deg/s for the angular measurements rates which are in good agreement with the recommended values of typical measurement modeling accuracies for Deep Space Networks. Although preliminary navigation accuracy guidelines are provided through this work, it is expected to give more practical insights into preparing the Korea's future lunar mission, especially for developing flight dynamics subsystem.

Implementation of Drug Delivery Constitution for Inpatient based on the Position Tracking System

  • Kim, Jeong-lae;Yoon, Su-yeon;Gil, Sang-hee;Park, Bo-geun;Jeong, Hyun-woo
    • International Journal of Advanced Culture Technology
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    • 제9권4호
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    • pp.402-408
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    • 2021
  • We are designed the delivery constitution technique that is to be measure the safe RFID statusof thewireless delivery system level (WDSL) on the delivery system tracking system. The delivery system level condition by the delivery system tracking system is organized with the RFID system. As to inspection a wireless network of the wireless network, we are found of the delivery value with wireless network by the upper take form. The concept of delivery system level is organized the reference of wireless level for delivery signal by the delivery RFID tracking system. Further, symbolizing a safe deliveryof the WDSL of the medium-minimum interval of the RFID tracking system, and the delivery wireless network RFID that was the delivery value of the far delivery of the DSTS-FA-φMED-MIN with 5.80±1.20 units, that was the delivery value of the convenient delivery of the DSTS-CO-φMED-MIN with 4.06±(-0.04) units, that was the delivery value of the flank delivery of the DSTS-φMED-MIN with 0.91±0.07 units, that was the delivery value of the vicinage delivery of the DSTS-VI-φMED-MIN with 0.18±(-0.03) units. The RFID will be to look into at the safe of the RFID tracking systemwith wireless network bythe delivery system level on the WDSL that is supply the wireless tracking system by the delivery system level system. We will be possible make to curb of a tracking system that to put the wireless signal and to use of the delivery data of RFID level by the delivery system.

모자이크 배경이미지 추출과 적응적 신경망을 이용한 다중 보행자 추적 시스템에 관한 연구 (A Study on Multiple Target Tracking Using Adaptive Neural Network and Mosaic Background Extraction)

  • 서창진;양황규
    • 한국정보통신학회논문지
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    • 제7권8호
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    • pp.1802-1808
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    • 2003
  • 본 논문은 자동 보행자 추적 시스템에 필요한 배경 이미지를 추출하는 방법과 추출되어진 배경 이미지를 이용하여 보행자를 탐지하고 적응적 신경망을 이용하여 보행자의 이동 궤적을 추적하는 시스템을 구현하였다. 본 논문은 고스트(ghost) 현상을 극복하기 위하여 모자이크 배경 이미지 추출 법으로 배경 이미지를 추출하였으며, 보행자의 탐지에 차영상 분석법을 기반으로 하여 보행자를 탐지하였다. ART2 네트워크는 프레임에 존재하는 이동 물체의 중심점을 탐지할 수 있다. 그리고, 이전 프레임에서 탐지되어진 물체의 정보를 이용하여 물체의 이동궤적을 추적할 수 있다. 제안하는 방법으로 실험한 결과 비강체(non­rigid)형태 운동을 하는 보행자를 탐지하고 그 궤적 추적에 대한 실시간 시스템 구성의 가능성에 대하여 알 수 있었다.

A Tracking-by-Detection System for Pedestrian Tracking Using Deep Learning Technique and Color Information

  • Truong, Mai Thanh Nhat;Kim, Sanghoon
    • Journal of Information Processing Systems
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    • 제15권4호
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    • pp.1017-1028
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    • 2019
  • Pedestrian tracking is a particular object tracking problem and an important component in various vision-based applications, such as autonomous cars and surveillance systems. Following several years of development, pedestrian tracking in videos remains challenging, owing to the diversity of object appearances and surrounding environments. In this research, we proposed a tracking-by-detection system for pedestrian tracking, which incorporates a convolutional neural network (CNN) and color information. Pedestrians in video frames are localized using a CNN-based algorithm, and then detected pedestrians are assigned to their corresponding tracklets based on similarities between color distributions. The experimental results show that our system is able to overcome various difficulties to produce highly accurate tracking results.

네트워크 기반 이동로봇에 대한 이득 스케줄러 제어 (Gain Scheduler Control for Networked Mobile Robot)

  • 윤상석;박기환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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    • pp.315-318
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    • 2005
  • This paper characterizes the performance for a remote path tracking control of the mobile robot in IP network viamiddleware. The middleware is used to alleviate the effect of the delay time on a mobile robot path tracking in Network-Based Control environment. The middleware also can be implemented in a modular structure. Thus, a controller upgrade or modification for other types of network protocols or different control objectives can be achieved easily. A case study on a mobile robot path-tracking with IP network delays is described. The effectiveness of the proposed approach is verified by experimental results.

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가상링크 기반의 ROBOKER 머리의 실시간 대상체 추종 성능 향상을 위한 신경망 제어 (Neural Network Compensation for Improvement of Real-Time Moving Object Tracking Performance of the ROBOKER Head with a Virtual Link)

  • 김동민;최호진;이근형;정슬
    • 제어로봇시스템학회논문지
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    • 제15권7호
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    • pp.694-699
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    • 2009
  • This paper presents the implementation of the real-time object tracking control of the ROBOKER head. The visual servoing technique is used to track the moving object, but suffers from ill-estimated Jacobian of the virtual link design. To improve the tracking performance, the RBF(Radial Basis Function) network is used to compensate for uncertainties in the kinematics of the robot head in on-line fashion. The reference compensation technique is employed as a neural network control scheme. Performances of three schemes, the kinematic based scheme, the Jacobian based scheme, and the neural network compensation scheme are verified by experimental studies. The neural compensation scheme performs best.

Neural Network Compensation for Impedance Force Controlled Robot Manipulators

  • Jung, Seul
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제14권1호
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    • pp.17-25
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    • 2014
  • This paper presents the formulation of an impedance controller for regulating the contact force with the environment. To achieve an accurate force tracking control, uncertainties in both robot dynamics and the environment require to be addressed. As part of the framework of the proposed force tracking formulation, a neural network is introduced at the desired trajectory to compensate for all uncertainties in an on-line manner. Compensation at the input trajectory leads to a remarkable structural advantage in that no modifications of the internal force controllers are required. Minimizing the objective function of the training signal for a neural network satisfies the desired force tracking performance. A neural network actually compensates for uncertainties at the input trajectory level in an on-line fashion. Simulation results confirm the position and force tracking abilities of a robot manipulator.

On the Design of Geodetic SVLBI Satellite Orbit and Its Tracking Network

  • Erhu, Wei;Jingnan, Liu;N, Kulkarni M.;Sandor, Frey
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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    • pp.505-510
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    • 2006
  • SVLBI (Space Very Long Baseline Interferometry) has some important potential applications in geodesy and geodynamics, for which one of the most difficult tasks is to precisely determine the orbit of SVLBI satellite. This paper studies several technologies which possibly will be able to determine the orbit of space VLBI satellite. And then, according to the sorts and characteristicsof satellite and the requirements for geodetic study and the geometry of GNSS (GPS, GALILEO) satellite to track the space VLBI satellite, the six Keplerian elements of SVLBI satellite (TEST-SVLBI) are determined. A program is designed to analyze the coverage area of the space of different heights by the stations of the network, with which the tracking network of TEST-SVLBI is designed. The efficiency of tracking TEST-SVLBI by the network is studied, and the results are presented.

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