• 한국화재소방학회논문지
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• 제27권5호
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• pp.15-18
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• 2013

본 연구는 자연 발생적인 화재 및 방화자에 의한 화재를 탐지하는 고효율 저비용의 옥외형 화재경보시스템으로 중소문화재, 천연기념물 및 옥외 시설물 등 화재 발생 시 관리 감시가 취약한 곳을 대상으로 한 소방시스템의 옥외 적용시 성능 및 시험에 대한 것이다. 재래적 화재감지시스템으로부터 탈피하여 지능적인 이동형 무인 화재감지시스템의 도입을 위해 화재경보시스템 성능시험, 기능시험, 옥외 환경시험, 불꽃시험 및 EMI/EMS 적합시험 등을 실시하였다. 성능시험, 기능시험, 불꽃시험 및 옥외방치시험을 3개월간 실시한바 양호하였고, 온도변화 성능시험도 $-30{\sim}70^{\circ}C$에서 양호하였으며 EMI/EMS 시험도 적합하였다. 불꽃검출거리는 75 m까지 증가되었고 대기모드 전원은 4시간 증가, 운영모드 전원에서의 동작시간은 3일까지 가능하였으며 센서뿐만 아니라 영상으로 상황을 인지하는데 적합함을 확인하였다.

• 디지털콘텐츠학회 논문지
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• 제16권1호
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• pp.25-32
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• 2015

학교폭력 및 성폭력 등의 범죄가 증가되어감에 따라 범인 검거에 있어서 CCTV에 대한 의존도가 높아지고 있다. 그러나 항상 사람 노동력으로 감시하기에는 경제력 및 인력의 한계가 있어 최근에는 지능형 보안 시스템으로 관심이 높아지고 있다. 따라서 기존에 연구한 객체 행동 인식 기법을 확장하여 본 연구에서는 CCTV에 획득되는 영상으로부터 2~3 객체간의 폭력 행위를 감지하는 시스템을 제안한다. 배경영상과의 차연산 및 모폴로지를 통해 객체를 검출하고 인식하여 추적한다. 폭력행위의 특징을 이용하여 폭력행위 판단 근거를 제시하였다. 더욱이, 여러 폭력 상황에 대한 측정을 통해 보다 객관적인 판단 메트릭 임계값을 도출하였다. 이 값을 바탕으로 폭력 행위 인식 실험을 진행한 결과 80% 이상의 인식 성공률을 보였으며, 향후연구로 다수 군중이 있는 상황 등에서의 이상행위 감지 시스템에 대한 연구가 남아있다.

• 한국군사과학기술학회지
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• 제10권3호
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• pp.139-147
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• 2007

In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.

• 한국정보통신학회논문지
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• 제25권10호
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• pp.1330-1336
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• 2021

모바일 환경에서 크게 성장한 것 중 하나는 YouTube와 같은 미디어 공유 플랫폼이다. 이는 기존의 TV로만 가능한 방송프로그램을 네트워크가 연결된 PC 및 모바일을 통하여 원하는 것을 골라 보고, 사용자들은 자신이 가진 미디어 콘텐츠를 공유하여 커뮤니케이션하는 플랫폼이다. 현재는 모바일과 TV 방송이 동일하게 시청이 가능한 시대이지만 TV와 모바일에 전송되는 영상과 실시간 화면이 실제 상황과는 다르게 시간차가 있다. 이 시간차를 실제시간과 동일하게 구현되기를 원하고, 언제든 자유로운 환경에서 방송할 수 있는 시스템이 요구되고 있다. 이에, 본 논문에서는 모바일 환경에서 방송시스템을 설계 및 구현하였다. 처리방식 개선으로 인한 지연 시간차를 줄이는 결과를 얻었다.

• ETRI Journal
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• 제42권1호
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• pp.78-89
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• 2020

Human activity recognition (HAR) has become effective as a computer vision tool for video surveillance systems. In this paper, a novel biometric system that can detect human activities in 3D space is proposed. In order to implement HAR, joint angles obtained using an RGB-depth sensor are used as features. Because HAR is operated in the time domain, angle information is stored using the sliding kernel method. Haar-wavelet transform (HWT) is applied to preserve the information of the features before reducing the data dimension. Dimension reduction using an averaging algorithm is also applied to decrease the computational cost, which provides faster performance while maintaining high accuracy. Before the classification, a proposed thresholding method with inverse HWT is conducted to extract the final feature set. Finally, the K-nearest neighbor (k-NN) algorithm is used to recognize the activity with respect to the given data. The method compares favorably with the results using other machine learning algorithms.

• IEIE Transactions on Smart Processing and Computing
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• 제6권4호
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• pp.262-268
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• 2017

Intelligent video surveillance systems have been developed to monitor global areas and find specific target objects using a large-scale database. However, person re-identification presents some challenges, such as pose change and occlusions. To solve the problems, this paper presents an improved person re-identification method using sparse representation and saliency-based dictionary construction. The proposed method consists of three parts: i) feature description based on salient colors and textures for dictionary elements, ii) orthogonal atom selection using cosine similarity to deal with pose and viewpoint change, and iii) measurement of reconstruction error to rank the gallery corresponding a probe object. The proposed method provides good performance, since robust descriptors used as a dictionary atom are generated by weighting some salient features, and dictionary atoms are selected by reducing excessive redundancy causing low accuracy. Therefore, the proposed method can be applied in a large scale-database surveillance system to search for a specific object.

• 디지털산업정보학회논문지
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• 제12권4호
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• pp.1-12
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• 2016

Digital imaging technology has developed into a state-of-the-art IT convergence, composite industry beyond the limits of the multimedia industry, especially in the field of smart object recognition, face - Application developed various techniques have been actively studied in conjunction with the phone. Recently, face recognition technology through the object recognition technology and evolved into intelligent video detection recognition technology, image recognition technology object detection recognition process applies to skills through is applied to the IP camera, the image object recognition technology with face recognition and active research have. In this paper, we first propose the necessary technical elements of the human factor technology trends and look at the human object recognition based spFACS (Smile Progress Facial Action Coding System) for detecting smiles study plan of the image recognition technology recognizes objects. Study scheme 1). ASM algorithm. By suggesting ways to effectively evaluate psychological research skills through the image object 2). By applying the result via the face recognition object to the tooth area it is detected in accordance with the recognized facial expression recognition of a person demonstrated the effect of extracting the feature points.

• 전기학회논문지
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• 제65권3호
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• pp.477-486
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• 2016

This paper presents the area classification, identification, and tracking for multiple moving objects with the similar colors. To do this, first, we use the GMM(Gaussian Mixture Model)-based background modeling method to detect the moving objects. Second, we propose the use of the binary and morphology of image in order to eliminate the shadow and noise in case of detection of the moving object. Third, we recognize ROI(region of interest) of the moving object through labeling method. And, we propose the area classification method to remove the background from the detected moving objects and the novel method for identifying the classified moving area. Also, we propose the method for tracking the identified moving object using Kalman filter. To the end, we propose the effective tracking method when detecting the multiple objects with the similar colors. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• 한국위성정보통신학회논문지
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• 제12권2호
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• pp.56-60
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• 2017

본 논문은 영상처리 기반의 낙상 감지 알고리즘의 설계 및 구현에 관한 내용을 기술한다. 영상처리 기반의 낙상 감지 알고리즘은 카메라로 획득한 입력 영상을 그레이 스케일 변환 후 배경차분과 이진화를 통해 객체를 분리하고, 라벨링을 통해 인체를 인식한다. 인식된 인체는 출력 영상으로 확인이 가능하며 낙상을 감지하게 되면 알람이 발생한다. 컴퓨터 시뮬레이션을 통하여 제안한 알고리즘을 실험한 결과 90%의 검출율을 보여주었다. DSP 영상처리 보드에 구현한 시제품 시험을 통하여 기능을 검증함으로서 실용화 가능성을 확인하였다.

• International Journal of Advanced Culture Technology
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• 제6권4호
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• pp.190-194
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• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.