• Title/Summary/Keyword: Vision Based Monitoring

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Pose Estimation of an Object from X-ray Images Based on Principal Axis Analysis

  • Roh, Young-Jun;Cho, Hyung-Suck
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.97.4-97
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    • 2002
  • 1. Introduction Pose estimation of a three dimensional object has been studied in robot vision area, and it is needed in a number of industrial applications such as process monitoring and control, assembly and PCB inspection. In this research, we propose a new pose estimation method based on principal axes analysis. Here, it is assumed that the locations of x-ray source and the image plane are predetermined and the object geometry is known. To this end, we define a dispersion matrix of an object, which is a discrete form of inertia matrix of the object. It can be determined here from a set of x-ray images, at least three images are required. Then, the pose information is obtained fro...

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A Research of CNN-based Object Detection for Multiple Object Tracking in Image (영상에서 다중 객체 추적을 위한 CNN 기반의 다중 객체 검출에 관한 연구)

  • Ahn, Hyochang;Lee, Yong-Hwan
    • Journal of the Semiconductor & Display Technology
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    • v.18 no.3
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    • pp.110-114
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    • 2019
  • Recently, video monitoring system technology has been rapidly developed to monitor and respond quickly to various situations. In particular, computer vision and related research are being actively carried out to track objects in the video. This paper proposes an efficient multiple objects detection method based on convolutional neural network (CNN) for multiple objects tracking. The results of the experiment show that multiple objects can be detected and tracked in the video in the proposed method, and that our method is also good performance in complex environments.

A Worker-Driven Approach for Opening Detection by Integrating Computer Vision and Built-in Inertia Sensors on Embedded Devices

  • Anjum, Sharjeel;Sibtain, Muhammad;Khalid, Rabia;Khan, Muhammad;Lee, Doyeop;Park, Chansik
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.353-360
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    • 2022
  • Due to the dense and complicated working environment, the construction industry is susceptible to many accidents. Worker's fall is a severe problem at the construction site, including falling into holes or openings because of the inadequate coverings as per the safety rules. During the construction or demolition of a building, openings and holes are formed in the floors and roofs. Many workers neglect to cover openings for ease of work while being aware of the risks of holes, openings, and gaps at heights. However, there are safety rules for worker safety; the holes and openings must be covered to prevent falls. The safety inspector typically examines it by visiting the construction site, which is time-consuming and requires safety manager efforts. Therefore, this study presented a worker-driven approach (the worker is involved in the reporting process) to facilitate safety managers by developing integrated computer vision and inertia sensors-based mobile applications to identify openings. The TensorFlow framework is used to design Convolutional Neural Network (CNN); the designed CNN is trained on a custom dataset for binary class openings and covered and deployed on an android smartphone. When an application captures an image, the device also extracts the accelerometer values to determine the inclination in parallel with the classification task of the device to predict the final output as floor (openings/ covered), wall (openings/covered), and roof (openings / covered). The proposed worker-driven approach will be extended with other case scenarios at the construction site.

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Development of Population-based Prevention Strategies for Childhood Obesity: Applied WHO Model (아동.청소년 비만 예방을 위한 인구기반 예방 전략 개발:WHO 모형의 적용)

  • Kim, Ki-Rang;Lee, Eun-Young;Kim, Hye-Ryun
    • Korean Journal of Health Education and Promotion
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    • v.28 no.3
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    • pp.43-55
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    • 2011
  • Objectives: The objectives of this study were to describe population-based prevention strategies for childhood obesity and to discuss its application in a city in Korea. Methods: Literature review and empirical findings for ongoing programs were performed to develop population-based prevention strategies for childhood obesity with the framework and principles of WHO population-based prevention strategies for childhood obesity. Results: The developed framework had five key strategies (supportive policies, supportive environment, supportive program, strategic development & leadership, and monitoring & evaluation) under hierarchic objectives (long-term, middle-term and short-term) with the vision of healthy growth and development of all children and youth. Each strategy included evidence-based action plans with WHO principles. Conclusions: The developed strategies have advanced the existing strategies for childhood obesity prevention by providing the sustainable and systematic framework and action plans based on ecological approach. Further, the feasibility for operating the strategies needs to be verified.

Position Improvement of a Mobile Robot by Real Time Tracking of Multiple Moving Objects (실시간 다중이동물체 추적에 의한 이동로봇의 위치개선)

  • Jin, Tae-Seok;Lee, Min-Jung;Tack, Han-Ho;Lee, In-Yong;Lee, Joon-Tark
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.2
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    • pp.187-192
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    • 2008
  • The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human Jollowing by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

A Study on Multi-Object Tracking Method using Color Clustering in ISpace (컬러 클러스터링 기법을 이용한 공간지능화의 다중이동물체 추척 기법)

  • Jin, Tae-Seok;Kim, Hyun-Deok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.11
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    • pp.2179-2184
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    • 2007
  • The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. This paper described appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

Video Motion Analysis for Sudden Death Detection During Sleeping (수면 중 돌연사 감지를 위한 비디오 모션 분석 방법)

  • Lee, Seung Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.10
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    • pp.603-609
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    • 2018
  • Sudden death during sleep often occurs in different age groups. To prevent an unexpected sudden death, sleep monitoring is required. This paper presents a video analysis method to detect sudden death without using any attachable sensors. In the proposed method, a motion magnification technique detects even very subtle motion during sleep. If the magnification cannot detect motion, the proposed method readily decides on abnormal status (possibly sudden death). Experimental results on two kinds of sleep video show that motion magnification-based video analysis could be useful for discriminating sleep (with very subtle motion) from sudden death.

Dynamic torsional response measurement model using motion capture system

  • Park, Hyo Seon;Kim, Doyoung;Lim, Su Ah;Oh, Byung Kwan
    • Smart Structures and Systems
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    • v.19 no.6
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    • pp.679-694
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    • 2017
  • The complexity, enlargement and irregularity of structures and multi-directional dynamic loads acting on the structures can lead to unexpected structural behavior, such as torsion. Continuous torsion of the structure causes unexpected changes in the structure's stress distribution, reduces the performance of the structural members, and shortens the structure's lifespan. Therefore, a method of monitoring the torsional behavior is required to ensure structural safety. Structural torsion typically occurs accompanied by displacement, but no model has yet been developed to measure this type of structural response. This research proposes a model for measuring dynamic torsional response of structure accompanied by displacement and for identifying the torsional modal parameter using vision-based displacement measurement equipment, a motion capture system (MCS). In the present model, dynamic torsional responses including pure rotation and translation displacements are measured and used to calculate the torsional angle and displacements. To apply the proposed model, vibration tests for a shear-type structure were performed. The torsional responses were obtained from measured dynamic displacements. The torsional angle and displacements obtained by the proposed model using MCS were compared with the torsional response measured using laser displacement sensors (LDSs), which have been widely used for displacement measurement. In addition, torsional modal parameters were obtained using the dynamic torsional angle and displacements obtained from the tests.

Transfer Learning Based Real-Time Crack Detection Using Unmanned Aerial System

  • Yuvaraj, N.;Kim, Bubryur;Preethaa, K. R. Sri
    • International Journal of High-Rise Buildings
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    • v.9 no.4
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    • pp.351-360
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    • 2020
  • Monitoring civil structures periodically is necessary for ensuring the fitness of the structures. Cracks on inner and outer surfaces of the building plays a vital role in indicating the health of the building. Conventionally, human visual inspection techniques were carried up to human reachable altitudes. Monitoring of high rise infrastructures cannot be done using this primitive method. Also, there is a necessity for more accurate prediction of cracks on building surfaces for ensuring the health and safety of the building. The proposed research focused on developing an efficient crack classification model using Transfer Learning enabled EfficientNet (TL-EN) architecture. Though many other pre-trained models were available for crack classification, they rely on more number of training parameters for better accuracy. The TL-EN model attained an accuracy of 0.99 with less number of parameters on large dataset. A bench marked METU dataset with 40000 images were used to test and validate the proposed model. The surfaces of high rise buildings were investigated using vision enabled Unmanned Arial Vehicles (UAV). These UAV is fabricated with TL-EN model schema for capturing and analyzing the real time streaming video of building surfaces.

Interface of Tele-Task Operation for Automated Cultivation of Watermelon in Greenhouse

  • Kim, S.C.;Hwang, H.
    • Journal of Biosystems Engineering
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    • v.28 no.6
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    • pp.511-516
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    • 2003
  • Computer vision technology has been utilized as one of the most powerful tools to automate various agricultural operations. Though it has demonstrated successful results in various applications, the current status of technology is still for behind the human's capability typically for the unstructured and variable task environment. In this paper, a man-machine interactive hybrid decision-making system which utilized a concept of tole-operation was proposed to overcome limitations of computer image processing and cognitive capability. Tasks of greenhouse watermelon cultivation such as pruning, watering, pesticide application, and harvest require identification of target object. Identifying water-melons including position data from the field image is very difficult because of the ambiguity among stems, leaves, shades. and fruits, especially when watermelon is covered partly by leaves or stems. Watermelon identification from the cultivation field image transmitted by wireless was selected to realize the proposed concept. The system was designed such that operator(farmer), computer, and machinery share their roles utilizing their maximum merits to accomplish given tasks successfully. And the developed system was composed of the image monitoring and task control module, wireless remote image acquisition and data transmission module, and man-machine interface module. Once task was selected from the task control and monitoring module, the analog signal of the color image of the field was captured and transmitted to the host computer using R.F. module by wireless. Operator communicated with computer through touch screen interface. And then a sequence of algorithms to identify the location and size of the watermelon was performed based on the local image processing. And the system showed practical and feasible way of automation for the volatile bio-production process.