• 전기학회논문지
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• 제67권2호
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• pp.314-324
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• 2018

This paper proposes a linear distributed target tracking filter for multiple unmanned aerial vehicles(UAVs) sharing their passive sensor measurements through communication channels. Different from the conventional nonlinear filtering schemes, the distributed passive target tracking problem is newly formulated within the framework of a linear robust state estimation theory incorporated with a linear uncertain measurement equation including the coordinate transform uncertainty. To effectively cope with the performance degradation due to the coordinate transform uncertainty, a linear consistent robust Kalman filter(CRKF) theory is devised and applied for designing a distributed passive target tracking filter. Through the simulations for typical UAV surveillance mission, the superior performance of the proposed method over the existing schemes of distributed passive target tracking are demonstrated.

• 한국항행학회논문지
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• 제13권2호
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• pp.252-256
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• 2009

본 논문에서는 산재되어있는 비상등을 운용관리센터에서 항시 점검 및 관리할 수 있고, 데이터 병목현상에 구애받지 않는 안정된 데이터 통신이 가능한 클러스터 구조형 감시망을 이용하여 비상등감시장치를 설치함에 있어 비상등 위치에 구애받음 없이 비상등의 감시장치를 설치할 수 있고, 감시 통신망을 구축함에 있어 게이트웨이로 지정된 감시장치가 고장나더라도 사각지대 없이 비상등의 상태를 감시 및 관리가 가능한 비상등관리시스템을 제안한다.

• International Journal of Contents
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• 제16권3호
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• pp.1-17
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• 2020

Human motion recognition is essential for user-centric services such as surveillance-based security, elderly condition monitoring, exercise tracking, daily calories expend analysis, etc. It is typically based on the movement data analysis such as the acceleration and angular velocity of a target user. The existing motion recognition studies are only intended to measure the basic information (e.g., user's stride, number of steps, speed) or to recognize single motion (e.g., sitting, running, walking). Thus, a new mechanism is required to identify the transition of single motions for assessing a user's consecutive motion more accurately as well as recognizing the user's body and surrounding situations arising from the motion. Thus, in this paper, we collect the human movement data through Android smartphones in real time for five targeting single motions and propose a mechanism to recognize a consecutive motion including transitions among various motions and an occurred situation, with the state transition model to check if a vulnerable (life-threatening) condition, especially for the elderly, has occurred or not. Through implementation and experiments, we demonstrate that the proposed mechanism recognizes a consecutive motion and a user's situation accurately and quickly. As a result of the recognition experiment about mix sequence likened to daily motion, the proposed adoptive weighting method showed 4% (Holding time=15 sec), 88% (30 sec), 6.5% (60 sec) improvements compared to static method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.361-364
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• 2007

A small sized device with computing, communicating, sensing capability is changing our life. It will be deployed in the world and acquire a lot of data from the world. It is used for various applications such as military surveillance, environmental monitoring, structure health monitoring, building management, asset tracking, etc. In this paper we focus on USN middleware for asset tracking. A mobile asset is moving here and there within a specific area. The USN middleware tracks the mobile assets in real-time by using sensor nodes and notify their current positions to a user. To achieve the goal, the USN middleware provides some features related to the positions of mobile assets.. They are storing location data by using 3D indexing method, retrieving them by using spatio-temporal query, making trace of an asset, and retrieving the history data of an asset. In the paper, we developed USN middleware to adapt the requirements of asset tracking. It can help users increase the efficiency of their business related to mobile assets and make a valuable decision.

• 센서학회지
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• 제14권4호
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• pp.278-285
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• 2005

This paper describes techniques of camera calibration and artificial landmarks detection for the automatic charging of a mobile robot, equipped with a fish-eye camera in the direction of its operation for movement or surveillance purposes. For its identification from the surrounding environments, three landmarks employed with infrared LEDs, were installed at the charging station. When the robot reaches a certain point, a signal is sent to the LEDs for activation, which allows the robot to easily detect the landmarks using its vision camera. To eliminate the effects of the outside light interference during the process, a difference image was generated by comparing the two images taken when the LEDs are on and off respectively. A fish-eye lens was used for the vision camera of the robot but the wide-angle lens resulted in a significant image distortion. The radial lens distortion was corrected after linear perspective projection transformation based on the pin-hole model. In the experiment, the designed system showed sensing accuracy of ${\pm}10$ mm in position and ${\pm}1^{\circ}$ in orientation at the distance of 550 mm.

• 한국광학회지
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• 제18권2호
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• pp.135-141
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• 2007

완전한 2차원 배열을 갖는 중적외선 대역의 $320\times240$ 검출기를 사용하는 3세대 열상 장비의 설계 및 제작은 이차원 배열 검출기 제작 기술의 발달과 영상 신호처리 기술의 진전으로 인해 최근 더욱 더 활발히 이루어지고 있다. 본 논문은 다양한 응용 분야에서 적외선 센서로 사용될 수 있도록 하기 위하여 소형 경량화 제작을 목표로 한 3세대 열상장비의 이중 배율 적외선 카메라의 설계와 Defocus용 셔터 렌즈에 의한 영상기반 불균일 보정 방식에 대해 다룬다.

• 센서학회지
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• 제29권3호
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• pp.194-200
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• 2020

Human detection is an important aspect in many video-based sensing and monitoring systems. Studies have been actively conducted for the automatic detection of humans in camera images, and various methods have been proposed. However, there are still problems in terms of performance and computational cost. In this paper, we describe a method for efficient human detection in the field of view of a camera, which may be static or moving, through multiple processing steps. A detection line is designated at the position where a human appears first in a sensing area, and only the one-dimensional gray pixel values of the line are monitored. If any noticeable change occurs in the detection line, corner detection and optical flow computation are performed in the vicinity of the detection line to confirm the change. When significant changes are observed in the corner numbers and optical flow vectors, the final determination of human presence in the monitoring area is performed using the Histograms of Oriented Gradients method and a Support Vector Machine. The proposed method requires processing only specific small areas of two consecutive gray images. Furthermore, this method enables operation not only in a static condition with a fixed camera, but also in a dynamic condition such as an operation using a camera attached to a moving vehicle.

• 한국위성정보통신학회논문지
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• 제9권4호
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• pp.26-31
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• 2014

본 논문은 컬러 영상에서 색상과 움직임 정보를 이용하여 후보영역을 특정하고 연기의 특성들을 추출하여 신경망을 사용한 검출의 성능을 분석하여 제시한다. 기존 연기 검출 알고리즘에서는 연기의 움직임, 색상을 분석하여 후보영역으로 특정하고 그 영역 안에서 연기의 여러 특성을 분석 하는 방법을 이용한다. 하지만 대부분 처음 발생하는 연기의 색상조건을 고려하지 않았기 때문에 조기 검출에는 적절하지 못하다. 본 논문은 연기의 색상과 움직임의 특성을 분석하여 그에 알맞은 방법을 적용하여 후보영역을 폭넓게 결정하고 그 영역 내에서 연기의 확산과 투명성을 인공신경망에 적용시킴으로써 나오는 성능을 분석하였다. 모의실험 결과는 91.31%의 검출율과, 2.62%의 오검출율 성능을 확인할 수 있었다.

• 한국산업융합학회 논문집
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• 제24권6_1호
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• pp.693-698
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• 2021

As technology advances, there is increasing need for research in different fields where this technology is applied. On of the most researched topic in computer vision is Human activity recognition (HAR), which has widely been implemented in various fields which include healthcare, video surveillance and education. We therefore present in this paper a human activity recognition system based on scale and rotation while employing the Kinect depth sensors to obtain the human skeleton joints. In contrast to previous approaches that use joint angles, in this paper we propose that each limb has an angle with the X, Y, Z axes which we employ as feature vectors. The use of the joint angles makes our system scale invariant. We further calculate the body relative direction in the egocentric coordinates in order to provide the rotation invariance. For the system parameters, we employ 8 limbs with their corresponding angles each having the X, Y, Z axes from the coordinate system as feature vectors. The extracted features are finally trained and tested with the Long short term memory (LSTM) Network which gives us an average accuracy of 98.3%.

• 한국환경보건학회지
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• 제48권3호
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• pp.131-137
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• 2022

Public interest has been increasing the focus on the management of exposure to pollutants and the related health effects. This study reviewed exposure assessment methodologies and addressed future directions. Exposure can be assessed by direct (exposure monitoring) or indirect approaches (exposure modelling). Exposure modelling is a cost-effective tool to assess exposure among individuals, but direct personal monitoring provides more accurate exposure data. There are several population exposure models: stochastic human exposure and dose simulation (SHEDS), air pollutants exposure (APEX), and air pollution exposure distributions within adult urban population in Europe (EXPOLIS). A South Korean population exposure model is needed since the resolution of ambient concentrations and time-activity patterns are country specific. Population exposure models could be useful to find the association between exposure to pollutants and adverse health effects in epidemiologic studies. With the advancement of sensor technology and the internet of things (IoT), exposure assessment could be applied in a real-time surveillance system. In the future, environmental health services will be useful to protect and promote human health from exposure to pollutants.