• Title/Summary/Keyword: Multi Object Detection

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Management System of On-line Mode Client-cluster (온라인 모드 클라이언트-클러스터 운영 시스템)

  • 박제호;박용범
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.4 no.2
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    • pp.108-113
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    • 2003
  • Research results have demonstrated that conventional client-server databases have scalability problem in the presence of many concurrent clients. The multi-tier architecture that exploits similarities in clients' object access behavior partitions clients into logical clusters according to their object request pattern. As a result, object requests that are served inside the clusters, server load and request response time can be optimized. Management of clustering by utilizing clients' access pattern-based is an important component for the system's goal. Off-line methods optimizes the quality of the global clustering, the necessary cost and clustering schedule needs to be considered and planned carefully in respect of stable system's performance. In this paper, we propose methods that detect changes in access behavior and optimize system configuration in real time. Finally this paper demonstrates the effectiveness of on-line change detection and results of experimental investigation concerning reconfiguration.

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Edge Grouping and Contour Detection by Delaunary Triangulation (Delaunary 삼각화에 의한 그룹화 및 외형 탐지)

  • Lee, Sang-Hyun;Jung, Byeong-Soo;Jeong, Je-Pyong;Kim, Jung-Rok;Moon, Kyung-li
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.1
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    • pp.135-142
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    • 2013
  • Contour detection is important for many computer vision applications, such as shape discrimination and object recognition. In many cases, local luminance changes turn out to be stronger in textured areas than on object contours. Therefore, local edge features, which only look at a small neighborhood of each pixel, cannot be reliable indicators of the presence of a contour, and some global analysis is needed. The novelty of this operator is that dilation is limited to Deluanary triangular. An efficient implementation is presented. The grouping algorithm is then embedded in a multi-threshold contour detector. At each threshold level, small groups of edges are removed, and contours are completed by means of a generalized reconstruction from markers. Both qualitative and quantitative comparison with existing approaches prove the superiority of the proposed contour detector in terms of larger amount of suppressed texture and more effective detection of low-contrast contour.

Improvement of Active Contour Model for Detection of Pulmonary Region in Medical Image (의학 영상에서 폐 영역 검출을 위한 Active Contour 모델 개선)

  • Kwon Y. J.;Won C. H.;Park H. J.;Lee J. H.;Lee S. H.;Cho J. H.
    • Journal of Korea Multimedia Society
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    • v.8 no.3
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    • pp.336-344
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    • 2005
  • In this paper, we extracted the contour of lung parenchyma on EBT images with the improved active contour model. The objects boundary in conventional active contour model can be extracted by controlling internal energy and external energy as energy minimizing form. However, there are a number of problems such as initialization and the poor convergence about concave part. Expecially, contour can not enter the concave region by discouraging characteristic about stretching and bending in internal energy. We controlled internal energy by moving local perpendicular bisector point of each control point in the contour and implemented the object boundary by minimizing energy with external energy The convergence of concave part could be efficiently implemented toward lung parenchyma region by this internal energy and both lung images for initial contour could also be detected by multi-detection method. We were sure this method could be applied detection of lung parenchyma region in medical image.

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The Change Detection from High-resolution Satellite Imagery Using Floating Window Method (이동창 방식에 의한 고해상도 위성영상에서의 변화탐지)

  • Im, Yeong-Jae;Ye, Cheol-Su;Kim, Gyeong-Ok
    • 한국지형공간정보학회:학술대회논문집
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    • 2002.11a
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    • pp.117-122
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    • 2002
  • Change detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, change detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by lower middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

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Design of Multi-Sensor-Based Open Architecture Integrated Navigation System for Localization of UGV

  • Choi, Ji-Hoon;Oh, Sang Heon;Kim, Hyo Seok;Lee, Yong Woo
    • Journal of Positioning, Navigation, and Timing
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    • v.1 no.1
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    • pp.35-43
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    • 2012
  • The UGV is one of the special field robot developed for mine detection, surveillance and transportation. To achieve successfully the missions of the UGV, the accurate and reliable navigation data should be provided. This paper presents design and implementation of multi-sensor-based open architecture integrated navigation for localization of UGV. The presented architecture hierarchically classifies the integrated system into four layers and data communications between layers are based on the distributed object oriented middleware. The navigation manager determines the navigation mode with the QoS information of each navigation sensor and the integrated filter performs the navigation mode-based data fusion in the filtering process. Also, all navigation variables including the filter parameters and QoS of navigation data can be modified in GUI and consequently, the user can operate the integrated navigation system more usefully. The conventional GPS/INS integrated system does not guarantee the long-term reliability of localization when GPS solution is not available by signal blockage and intentional jamming in outdoor environment. The presented integration algorithm, however, based on the adaptive federated filter structure with FDI algorithm can integrate effectively the output of multi-sensor such as 3D LADAR, vision, odometer, magnetic compass and zero velocity to enhance the accuracy of localization result in the case that GPS is unavailable. The field test was carried out with the UGV and the test results show that the presented integrated navigation system can provide more robust and accurate localization performance than the conventional GPS/INS integrated system in outdoor environments.

A Study on the Estimation of Multi-Object Social Distancing Using Stereo Vision and AlphaPose (Stereo Vision과 AlphaPose를 이용한 다중 객체 거리 추정 방법에 관한 연구)

  • Lee, Ju-Min;Bae, Hyeon-Jae;Jang, Gyu-Jin;Kim, Jin-Pyeong
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.7
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    • pp.279-286
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    • 2021
  • Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

A Study on Multi-Object Data Split Technique for Deep Learning Model Efficiency (딥러닝 효율화를 위한 다중 객체 데이터 분할 학습 기법)

  • Jong-Ho Na;Jun-Ho Gong;Hyu-Soung Shin;Il-Dong Yun
    • Tunnel and Underground Space
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    • v.34 no.3
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    • pp.218-230
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    • 2024
  • Recently, many studies have been conducted for safety management in construction sites by incorporating computer vision. Anchor box parameters are used in state-of-the-art deep learning-based object detection and segmentation, and the optimized parameters are critical in the training process to ensure consistent accuracy. Those parameters are generally tuned by fixing the shape and size by the user's heuristic method, and a single parameter controls the training rate in the model. However, the anchor box parameters are sensitive depending on the type of object and the size of the object, and as the number of training data increases. There is a limit to reflecting all the characteristics of the training data with a single parameter. Therefore, this paper suggests a method of applying multiple parameters optimized through data split to solve the above-mentioned problem. Criteria for efficiently segmenting integrated training data according to object size, number of objects, and shape of objects were established, and the effectiveness of the proposed data split method was verified through a comparative study of conventional scheme and proposed methods.

A Traffic Aware Demand-Wakeup MAC(TADW-MAC) Protocol for Wireless Sensor Networks (무선 센서 네트워크에서 트래픽에 적응적인 Demand-Wakeup MAC 프로토콜)

  • Kim, Hye-Yun;Kim, Seong-Cheol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.1
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    • pp.180-186
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    • 2017
  • In this paper we propose a traffic aware Demand Wakeup MAC(TADW-MAC) protocol, in which low data delay and high throughput can be achieved, for wireless sensor networks. With the TADW-MAC protocol, the problem of the DW-MAC protocol, which schedules only one packet to deliver during the Sleep period in a multi-hop transmission is resolved. DW-MAC is not adequate for the applications such as object tracking and fire detection, in which busty data should be transmitted in a limited time when an event occurs [6-8]. When an event occurs, duty cycle can be adjusted in the TADW-MAC protocol to get less energy consumption and low latency. The duty cycle mechanism has been widely used to save energy consumption of sensor node due to idle listening in wireless sensor networks. But additional delay in packet transmission may be increased in the mechanism. Our simulation results show that TADW-MAC outperforms RMAC and DW-MAC in terms of energy efficiency while achieving low latency.

A Study on Establishment Method of Smart Factory Dataset for Artificial Intelligence (인공지능형 스마트공장 데이터셋 구축 방법에 관한 연구)

  • Park, Youn-Soo;Lee, Sang-Deok;Choi, Jeong-Hun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.5
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    • pp.203-208
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    • 2021
  • At the manufacturing site, workers have been operating by inputting materials into the manufacturing process and leaving input records according to the work instructions, but product LOT tracking has been not possible due to many omissions. Recently, it is being carried out as a system to automatically input materials using RFID-Tag. In particular, the initial automatic recognition rate was good at 97 percent by automatically generating input information through RACK (TAG) ID and RACK input time analysis, but the automatic recognition rate continues to decrease due to multi-material RACK, TAG loss, and new product input issues. It is expected that it will contribute to increasing speed and yield (normal product ratio) in the overall production process by improving automatic recognition rate and real-time monitoring through the establishment of artificial intelligent smart factory datasets.

Preliminary Perfomances Anlaysis of 1.5-m Scale Multi-Purpose Laser Ranging System (1.5m급 다목적형 레이저 추적 시스템 예비 성능 분석)

  • Son, Seok-Hyeon;Lim, Jae-Sung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.49 no.9
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    • pp.771-780
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    • 2021
  • The space Debris laser ranging system is called to be a definite type of satellite laser ranging system that measures the distance to satellites. It is a system that performs POD (Precise Orbit Determination) by measuring time of flight by firing a laser. Distance precision can be measured in mm-level units, and it is the most precise system among existing systems. Currently, KASI has built SLR in Sejong and Geochang, and utilized SLR data to verify the precise orbits of the STSAT-2C and KOMASAT-5. In recent years, due to the fall or collision of space debris, its satellites have been threatened, and in terms of security, laser tracking of space objects is receiving great interest in order to protect their own space assets and protect the safety of the people. In this paper, a 1.5m-class main mirror was applied for the system design of a multipurpose laser tracking system that considers satellite laser ranging and space object laser tracking. System preliminary performance analysis was performed based on Link Budget analysis considering specifications of major components.