• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.87-95
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• 2020

Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.

• 한국위성정보통신학회논문지
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• 제12권1호
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• pp.101-106
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• 2017

In this paper, we present Emergency exit signs are installed to provide escape routes or ways in buildings like shopping malls, hospitals, industry, and government complex, etc. and various other places for safety purpose to aid people to escape easily during emergency situations. In case of an emergency situation like smoke, fire, bad lightings and crowded stamped condition at emergency situations, it's difficult for people to recognize the emergency exit signs and emergency doors to exit from the emergency building areas. This paper propose an automatic emergency exit sing recognition to find exit direction using a smart device. The proposed approach aims to develop an computer vision based smart phone application to detect emergency exit signs using the smart device camera and guide the direction to escape in the visible and audible output format. In this research, a CAMShift object tracking approach is used to detect the emergency exit sign and the direction information extracted using template matching method. The direction information of the exit sign is stored in a text format and then using text-to-speech the text synthesized to audible acoustic signal. The synthesized acoustic signal render on smart device speaker as an escape guide information to the user. This research result is analyzed and concluded from the views of visual elements selecting, EXIT appearance design and EXIT's placement in the building, which is very valuable and can be commonly referred in wayfinder system.

• 한국항공우주학회지
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• 제34권7호
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• pp.63-70
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• 2006

본 논문은 영상기반 헤드 트랙커에 인공 표식의 면적을 이용하는 연구를 기술하였다. 헤드 트랙커 체계는 병진운동과 회전운동으로 구성되어 있으며, 이들은 웹 카메라에 의하여 감지되었다. 감지된 영상은 영상처리 기법과 인공 신경망에 의하여 운동에 따른 결과를 만들게 된다. 헤드 트랙커가 사용될 항공기의 조종석의 특성상 병진운동은 헬멧의 특정 색을 추적하게 하였다. 회전 운동은 인공 신경망을 이용하여 추적하였으며, 헬멧에 표시된 두 가지 색의 면적 비율을 입력 값으로 사용하였다. 여기서 역전파 알고리즘과 RBFN을 사용하였다. 두 알고리즘은 머리의 움직임과 같은 비선형 체계를 분류하고 추적하는데 용이한 알고리즘으로 역전파 알고리즘은 피드백 특성을, RBFN은 확률적 특성을 이용한다. 본 논문에서는 회전운동에 어느 알고리즘이 더 적합한 알고리즘인지 비교하였다.

• Journal of Welding and Joining
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• 제34권2호
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• pp.59-66
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• 2016

The Gas Metal Arc(GMA) welding, called Metal Inert Gas(MIG) welding, has been an important component in manufacturing industries. A key technology for robotic welding processes is seam tracking system, which is critical to improve the welding quality and welding capacities. The objectives of this study were to develop the intelligent and cost-effective algorithms for image processing in GMA welding which based on the laser vision sensor. Welding images were captured from the CCD camera and then processed by the proposed algorithm to track the weld joint location. The proposed algorithms that commonly used at the present stage were verified and compared to obtain the optimal one for each step in image processing. Finally, validity of the proposed algorithms was examined by using weld seam images obtained with different welding environments for image processing. The results proved that the proposed algorithm was quite excellent in getting rid of the variable noises to extract the feature points and centerline for seam tracking in GMA welding and could be employed for general industrial application.

• 제어로봇시스템학회논문지
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• 제22권1호
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• pp.24-30
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• 2016

The accuracy of small and low-cost CCD cameras is insufficient to provide data for precisely tracking unmanned aerial vehicles (UAVs). This study shows how a quad rotor UAV can hover on a human targeted tracking object by using data from a CCD camera rather than imprecise GPS data. To realize this, quadcopter UAVs need to recognize their position and posture in known environments as well as unknown environments. Moreover, it is necessary for their localization to occur naturally. It is desirable for UAVs to estimate their position by solving uncertainty for quadcopter UAV hovering, as this is one of the most important problems. In this paper, we describe a method for determining the altitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from images captured by a fixed camera to localize a UAV. Using the a priori known path of a quadcopter UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's altitude. Since the equations are based on the geometric constraint equation, measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. Its performance is verified by a computer simulation and experiments.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 추계종합학술대회
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• pp.227-232
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• 2003

본 논문에서는 다양한 조명하에서 실시간으로 눈을 검출하고 추적하는 새로운 방법을 제안하고자 한다. 기존의 능동적 적외선을 이용한 눈 검출 및 추적 방법은 외부의 조명에 매우 민감하게 반응하는 문제점을 가지고 있으므로, 본 논문에서는 적외선 조명을 이용한 밝은 동공 효과와 전형적인 외형을 기반으로 한 사물 인식 기술을 결합하여 외부 조명의 간섭으로 밝은 동공 효과가 나타나지 않는 경우에도 견실하게 눈을 검출하고 추적 할 수 있는 방법을 제안한다. 눈 검출과 추적을 위해 SVM과 평균 이동 추적방법을 사용하였고, 적외선 조명과 카메라를 포함한 영상 획득 장치를 구성하여 제안된 방법이 효율적으로 다양한 조명하에서 눈 검출과 추적을 할 수 있음을 보여 주었다.

• 한국정보통신학회논문지
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• 제23권3호
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• pp.247-253
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• 2019

본 논문에서는 레이저 센서 시스템을 이용한 이동중의 사람들을 실시간으로 추종하는 새로운 방법을 제시하였다. 제시한 방법은 $r-{\theta}$로 표현되는 센서데이터를 x-y좌표로 표현되는 2차원 공간으로 표현이 가능하다. 이러한 이동중인 사람들에 대한 정보는 보행패턴과 입력 센서데이터 값에 의해서 이동중인 사람의 특징값을 이용하여 적용하였다. 레이저 센서 기반 사람 추적 방법은 기존의 영상기반의 얼굴인식 방법보다 간단하면서도 이점을 가지고 있다. 제안방법에선 이동궤적알고리즘 기반으로 이동중인 사람의 발목부위를 계측하였도록 하였다. 게다가 제안된 추적 시스템은 중첩된 상황에서도 사람을 강건하게 추적할 수 있도록 HMM 방법을 적용하였다. 적용한 방법을 검증하기 위하여 실제 시스템을 적용한 실험결과를 제시하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 학술대회지
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• pp.857-861
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• 2004

This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks (GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

• 정보처리학회논문지B
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• 제12B권3호
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• pp.273-282
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• 2005

실시간 객체 추적(Real-time object tracking)은 비디오 감시 시스템, 비전 기반 네비게이터와 같은 비전 응용 산업이 발달하면서 그 중요성이 더해지고 있는 분야이다. 객체 추적을 위해 많이 이용되고 있는 알고리즘으로 Mean-shift와 Condensation 알고리즘이 있다. Mean-shift 알고리즘을 기반으로 한 객체 추적 알고리즘은 구현이 간단하고, 적은 계산 복잡도를 갖는 장점이 있다. 따라서 실시간 객체 추적 시스템에 적합하다고 할 수 있지만, 지역 모드(Local mode)로 수렴하는 특성으로 인해 복잡한 환경(Cluttered environment)에서는 좋은 성능을 나타내지 못하는 단점을 가지고 있다. 반면, 여러 개의 후보들을 이용해 객체의 위치를 추정하는 Condensation 추적 알고리즘은 복잡한 환경에서 특정 객체를 추적하는데 많이 사용된다. 하지만 Condensation 알고리즘을 기반으로 한 추적 알고리즘은 정확한 추적을 하기 위해서 복잡도가 높은 객체 모델과 많은 수의 후보가 요구된다. 따라서 높은 복잡도를 갖게 되고, 이것으로 인해 복잡한 환경에서는 실시간 구현이 어렵다는 단점을 갖게 된다. 본 논문에서는, 복잡한 환경에서 실시간 객체 추적에 적합하도록 Condensation 알고리즘과 Mean-shift 알고리즘을 결합해서, 적은 수의 후보들을 이용하는 모델을 제안한다. 적은 수의 후보들을 이용하더라도, Mean-shift 알고리즘을 이용해 보다 높은 유사도를 가지는 후보들만을 이용함으로써, Condensation 알고리즘이나 Mean-shift 알고리즘만을 이용할 때보다 더 나은 성능을 얻을 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.168.1-168
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• 2001

This article describes a novel model-based compensating neural network (NN) model developed to be used in our active binocular head controller, which addresses both the kinematics and dynamics aspects in trying to precisely track a moving object of interest to keep it in view. The compensating NN model is constructed using two classes of self-tuning neural models: namely Neural Gas (NG) algorithm and SoftMax function networks. The resultant servo controller is shown to be able to handle the tracking problem with a minimum knowledge of the dynamic aspects of the system.