• Title/Summary/Keyword: Average-point Tracking

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Development and Application of Automatic Rainfall Field Tracking Methods for Depth-Area-Duration Analysis (DAD 분석을 위한 자동 강우장 탐색기법의 개발 및 적용)

  • Kim, Yeon Su;Song, Mi Yeon;Lee, Gi Ha;Jung, Kwan Sue
    • Journal of Korea Water Resources Association
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    • v.47 no.4
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    • pp.357-370
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    • 2014
  • This study aims to develop a rainfall field tracking method for depth-area-duration (DAD) analysis and assess whether the proposed tracking methods are able to properly estimate the maximum average areal rainfall (MAAR) within the study area during a rainfall period. We proposed three different rainfall field tracking algorithms (Box-tracking, Point-tracking, Advanced point-tracking) and then applied them to the virtual rainfall field with 1hr duration and also compared DAD curves of each method. In addition, we applied the three tracking methods and a traditional GIS-based tool to the typhoon 'Nari' rainfall event of the Yongdam-Dam watershed and then assess applicability of the proposed methods for DAD analysis. The results showed that Box-tracking was much faster than the other two tracking methods in terms of searching for the MAAR but it was impossible to describe rainfall spatial pattern during its tracking processes. On the other hand, both Point-tracking and Advanced point-tracking provided the MAAR by considering the spatial distribution of rainfall fields. In particular, Advanced point-tracking estimated the MAAR more accurately than Point-tracking in the virtual rainfall field, which has two rainfall centers with similar depths. The proposed automatic rainfall field tracking methods can be used as effective tools to analyze DAD relationship and also calculate areal reduction factor.

Basin-scale DAD Analysis using Grid-based Rain Search Method (격자기반의 호우탐색기법을 이용한 유역기반의 DAD 분석)

  • Kim, Youngkyu;Yu, Wansik;Kim, Yeonsu;Jeong, Anchul;Jung, Kwansue
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.236-236
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    • 2017
  • 본 연구에서는 강우의 시공간성을 파악할 수 있는 격자기반의 Average-point Tracking 프로그램을 이용하여 호우의 DAD(Depth-Area-Duration)를 분석하였다. IPCC 5차보고서에 따르면 1950년 이래로 다수의 극한 기상 및 기후 변화가 관측되었다. 그 중 일부는 인간의 활동과 관련된 것으로 많은 지역에서의 극한 호우 현상의 증가가 손꼽힌다. 이러한 극한 호우 현상 증가와 일부 저수지의 유출 증가 경향은 지역적 규모에서 홍수의 위험이 더 커졌음을 의미한다(Kim et al., 2016). 최근 이상기후 현상의 증가에 따른 강우양상의 변화로 게릴라성 집중 호우와 태풍의 빈도가 증가하고 있지만, 우리나라의 호우의 특성은 방위 및 진행방향에 따른 해석이 매우 복잡하여 강우를 정형화하기에 어려운 특징을 보인다. 또한 지속시간이 긴 호우의 경우에는 호우의 범위가 한반도 전체가 되는 특성 때문에 강우의 시 공간성과 관련된 관측 자료는 부족하며, 이러한 특성을 고려한 연구 또한 미진한 실정이다. 만약, 태풍과 같이 호우이동이 뚜렷한 경우, 기존의 적용되고 있는 유역중심의 DAD 분석 방법으로는 DAD 관계를 명확히 표현하기 어려우며 유역면적이 증가할수록 유역의 면적평균강우량의 오차도 증가하기 때문에 DAD 분석의 정확도는 낮아지게 된다. 따라서 본 연구에서는 호우의 형태와 이동을 고려하기 위해 시간에 따른 호우를 격자로 나누어 격자를 증가시키면서 면적평균최대강우량을 산정할 수 있는 Average-point Tracking 방법을 이용하여 DAD 분석을 실시하였다.

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Model-Following Control in Random Access Deviecs for Velocity Performance Enhancement (랜덤액세스 장치의 속도성능 향상을 위한 모델추종 제어기의 적용)

  • Lee, J.H;Park, K.H;Kim, S.H;Kwak, Y.K
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.1
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    • pp.115-126
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    • 1996
  • In the time optimal control problem, bang-bang control has been used becaese it is the theoretical time minimum solution. However, to improve tracking speed performance in the time optimal control, it is important to select a switching point accurately which makes the velocity zero near the target track. But it is not easy to select the swiching point accurately because of the damping coefficient variation and uncertainties of modeling an actual system. The Adaptive model following control(AMFC) is implemented to relieve the difficulty and inconvenience of this task. The AMFC and make the controlled plant follow as closely as possible to a desired reference model whose switching point can be calculated easily and accurately, assuring the error between the states of the reference model and those of the controlled plant appoaches zero. The hybrid control method composed of AMFC and PID is applied to a tracking actuator of the magneto optical disk drive(MODD) in random access devices to improve its slow tracking performance. According to the simulaion and experimental results, the average tracking time as small as 20ms is obtained for a 3.5 magneto-optical disk drive. The AMFC also can be applied for other random access devices to improve the average tracking performance.

DAD Analysis of Yongdam Dam Watershed Using the Cell-Based Automatic Rainfall Field Tracking Methods (격자기반의 자동 강우장 탐색기법을 활용한 용담댐 유역 DAD분석)

  • Song, Mi-Yeon;Jung, Kwan-Sue;Lee, Gi-Ha;Kim, Yeon-Su;Shin, Young-A
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.3
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    • pp.68-81
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    • 2014
  • This study aims to apply and evaluate the automatic DAD analysis method, which is able to establish the depth-area relationship more efficiently and accurately for point-to-areal rainfall conversion. First, the proposed automatic DAD analysis method tracks the expansion route of area from the storm center, and it is divided into Box-tracking, Point-tracking, Advanced point-tracking according to tracking method. After applying the proposed methods to 10 events occurred in Yongdam-watershed area, we confirmed that the Advanced point-tracking method makes it possible to estimate the maximum average areal rainfal(MAAR) more accurately with consideration of the storm movement and the multi-centered storm. In addition, Advanced point-tracking could reduce the errors of the estimated MAAR induced by increasing the area because it can estimate MAAR for each storm center and compare them at the same time. Finally, the DAD curve for the study area could be derived based on the DAD analysis of the selected 10 events.

Scale Invariant Single Face Tracking Using Particle Filtering With Skin Color

  • Adhitama, Perdana;Kim, Soo Hyung;Na, In Seop
    • International Journal of Contents
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    • v.9 no.3
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    • pp.9-14
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    • 2013
  • In this paper, we will examine single face tracking algorithms with scaling function in a mobile device. Face detection and tracking either in PC or mobile device with scaling function is an unsolved problem. Standard single face tracking method with particle filter has a problem in tracking the objects where the object can move closer or farther from the camera. Therefore, we create an algorithm which can work in a mobile device and perform a scaling function. The key idea of our proposed method is to extract the average of skin color in face detection, then we compare the skin color distribution between the detected face and the tracking face. This method works well if the face position is located in front of the camera. However, this method will not work if the camera moves closer from the initial point of detection. Apart from our weakness of algorithm, we can improve the accuracy of tracking.

Predictive Control of an Efficient Human Following Robot Using Kinect Sensor (Kinect 센서를 이용한 효율적인 사람 추종 로봇의 예측 제어)

  • Heo, Shin-Nyeong;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.9
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    • pp.957-963
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    • 2014
  • This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot end-point precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

Designing Real-time Observation System to Evaluate Driving Pattern through Eye Tracker

  • Oberlin, Kwekam Tchomdji Luther.;Jung, Euitay
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.421-431
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    • 2022
  • The purpose of this research is to determine the point of fixation of the driver during the process of driving. Based on the results of this research, the driving instructor can make a judgement on what the trainee stare on the most. Traffic accidents have become a serious concern in modern society. Especially, the traffic accidents among unskilled and elderly drivers are at issue. A driver should put attention on the vehicles around, traffic signs, passersby, passengers, road situation and its dashboard. An eye-tracking-based application was developed to analyze the driver's gaze behavior. It is a prototype for real-time eye tracking for monitoring the point of interest of drivers in driving practice. In this study, the driver's attention was measured by capturing the movement of the eyes in real road driving conditions using these tools. As a result, dwelling duration time, entry time and the average of fixation of the eye gaze are leading parameters that could help us prove the idea of this study.

Start Point Detection Method for Tracing the Injection Path of Steel Rebars (철근 사출 궤적 추적을 위한 시작지점 검출 방법)

  • Lee, Jun-Mock;Kang, Dae-Seong
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.6
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    • pp.9-16
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    • 2019
  • Companies that want to improve their manufacturing processes have recently introduced the smart factory, which is particularly noticeable. The ultimate goal is to maximize the area of the smart factory that performs the process of the production facility completely with minimal manual control and to minimize errors of reasoning. This research is a part of a project for unmanned production, management, packaging, and delivery management and the detection of the start point of rebars to perform the automatic calibration of the rollers through the tracking of the automated facilities of unmanned production. It must meet the requirement to accurately track the position from the start point to the end point. In order to improve the tracking performance, it is important to set the accurate start point. However, the probability of tracking errors is high depending on environments such as illumination and dust through the conventional time-based detection method. In this paper, we propose a starting point detection method using the average brightness change of high speed IR camera to reduce the errors according to the environments, As a result, its performance is improved by more than 15%.

Real-time Location Tracking System Using Ultrasonic Wireless Sensor Nodes (초음파 무선 센서노드를 이용한 실시간 위치 추적 시스템)

  • Park, Jong-Hyun;Choo, Young-Yeol
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.7
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    • pp.711-717
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    • 2007
  • Location information will become increasingly important for future Pervasive Computing applications. Location tracking system of a moving device can be classified into two types of architectures: an active mobile architecture and a passive mobile architecture. In the former, a mobile device actively transmits signals for estimating distances to listeners. In the latter, a mobile device listens signals from beacons passively. Although the passive architecture such as Cricket location system is inexpensive, easy to set up, and safe, it is less precise than the active one. In this paper, we present a passive location system using Cricket Mote sensors which use RF and ultrasonic signals to estimate distances. In order to improve accuracy of the passive system, the transmission speed of ultrasound was compensated according to air temperature at the moment. Upper and lower bounds of a distance estimation were set up through measuring minimum and maximum distances that ultrasonic signal can reach to. Distance estimations beyond the upper and the lower bounds were filtered off as errors in our scheme. With collecting distance estimation data at various locations and comparing each distance estimation with real distance respectively, we proposed an equation to compensate the deviation at each point. Equations for proposed algorithm were derived to calculate relative coordinates of a moving device. At indoor and outdoor tests, average location error and average location tracking period were 3.5 cm and 0.5 second, respectively, which outperformed Cricket location system of MIT.

Object Tracking Algorithm using Feature Map based on Siamese Network (Siamese Network의 특징맵을 이용한 객체 추적 알고리즘)

  • Lim, Su-Chang;Park, Sung-Wook;Kim, Jong-Chan;Ryu, Chang-Su
    • Journal of Korea Multimedia Society
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    • v.24 no.6
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    • pp.796-804
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    • 2021
  • In computer vision, visual tracking method addresses the problem of localizing an specific object in video sequence according to the bounding box. In this paper, we propose a tracking method by introducing the feature correlation comparison into the siamese network to increase its matching identification. We propose a way to compute location of object to improve matching performance by a correlation operation, which locates parts for solving the searching problem. The higher layer in the network can extract a lot of object information. The lower layer has many location information. To reduce error rate of the object center point, we built a siamese network that extracts the distribution and location information of target objects. As a result of the experiment, the average center error rate was less than 25%.