• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.507-508
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• 2018

본 논문에서는 라즈베리파이를 활용하여 야생조류의 행동에 반응하는 비전기반 야생조류 퇴치 장치를 구현하였다. 저가형 라즈베리파이 보드를 기반으로 카메라센서와 OpenCV 모션탐지기법을 활용하여 야생조류의 침입을 탐지하고, 그리고 야생조류가 소리별로 반응하는 데이터를 누적시키는 방법을 활용하여 효율적으로 퇴치하도록 개발하였다. 성능평가는 야생 직박구리와 박새를 포획하여 야외 실험장에서 진행하였고 실제 환경에서도 야생조류를 퇴치할 수 있다는 결과를 보여준다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.221-230
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• 2002

This paper presents a new moving object segmentation algorithm using markov random field. The algorithm is based on signal detection theory. That is to say, motion of moving object is decided by binary decision rule, and false decision is corrected by markov random field model. The procedure toward complete segmentation consists of two steps: motion detection and object segmentation. First, motion detection decides the presence of motion on velocity vector by binary decision rule. And velocity vector is generated by optical flow. Second, object segmentation cancels noise by Bayes rule. Experimental results demonstrate the efficiency of the presented method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.10a
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• pp.80-82
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• 2013

해상 물동량의 증가에 따라 선박들이 점차 대형화 되어 가고 있고 선박의 수 또한 지속적으로 늘어나고 있다. 이러한 현상은 곧 해양사고의 증가로 이어지고 있는데 이 중 인적과실에 의한 해양사고가 대부분의 원인으로 밝혀져 있다. 인적과실 중 항해나 당직근무 중 졸음에 의한 사고가 빈번한데 이를 방지하기 위하여 IMO(international maritime organization, 국제해사기구)에서는 선교 항해당직 경보시스템의 의무탑재를 시행하고 있다. 하지만 현행의 선교 항해당직 경보시스템은 재설정 방식에 따른 불편함 때문에 항해사들의 불만이 제기되고 있어 이에 대한 해소책으로 IMO에서는 모션센서를 선교 항해당직 경보시스템에 도입할 것을 권고하고 있다. 그러나 이 모션센서의 탐지기술이나 동작원리는 처음 육상용 화재경보시스템 혹은 보안시스템용으로 개발 및 제작되어진 것이므로 이를 특수한 조건인 선박의 항해당직에 적용할 때 야기될 수 있는 문제점이나 고려사항등을 검토해 볼 필요가 있다. 이 논문에서는 이 모션센서의 선교에서의 이상적인 구성, 필요한 기능, 적확한 작동여부, 모션센서와 압력센서나 음성인식센서와 같은 다른 수단과의 병용 등을 고려하여 모션센서의 최적기능 확보를 위한 성능기준을 제시하고자 한다.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.87-96
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• 2005

In this paper, a selective visual attention module based on motion stimuli is introduced for the purpose of detecting ROI(region of interest) or FOA(focus of attention) in motion pictures. Analysis of motion fields in our approach is in direct contrast to some of the previous studies of selective visual attention module. Motion that presents temporal visual saliency in an aspect between two successive frames is analyzed based on psychological studies in 'DORF(double opponent receptive fields)' and 'NF(noise filtration)' in MT(middle temporal cortex). Analyzed results are integrated based on the theory of 'motion integration' in MT to obtain a single conspicuous region. Experiments through a human subjective evaluation showed generally accepted results.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.189-196
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• 2008

In this paper, a CMOS digital image sensor, which consists of A/D conversion, motion estimation circuits, and an attention module for ROI (Region of Interest) detection is presented. The functions of A/D conversion and motion estimation are implemented by $0.6{\mu}m$ CMOS processing circuit as hardware, and the attention module is implemented outside the circuit as software currently. Attention modules are taken to improve limited applications of the smart image sensor. The current smart image sensor responses to the changes of intensity, and uses the integration time to estimate motion. Therefore it is limited in its applications. To make up for inherent property of the sensor from circuit design and extend its applications we decide to introduce perception solutions to the image sensor. Attention modules for still and moving images are employed to achieve such purposes. The suggested approach makes the smart image sensor available with additional functions for such cases that motion estimation or intensity changes are not observed. Experimental result shows the usefulness and extension of the image sensor.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.81-89
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• 2023

In modern society, blind people face difficulties in navigating common environments such as sidewalks, elevators, and crosswalks. Research has been conducted to alleviate these inconveniences for the visually impaired through the use of visual and audio aids. However, such research often encounters limitations when it comes to practical implementation due to the high cost of wearable devices, high-performance CCTV systems, and voice sensors. In this paper, we propose an artificial intelligence fusion algorithm that utilizes low-cost video sensors integrated into smartphones to help blind people safely navigate their surroundings during walking. The proposed algorithm combines motion capture and object detection algorithms to detect moving people and various obstacles encountered during walking. We employed the MediaPipe library for motion capture to model and detect surrounding pedestrians during motion. Additionally, we used object detection algorithms to model and detect various obstacles that can occur during walking on sidewalks. Through experimentation, we validated the performance of the artificial intelligence fusion algorithm, achieving accuracy of 0.92, precision of 0.91, recall of 0.99, and an F1 score of 0.95. This research can assist blind people in navigating through obstacles such as bollards, shared scooters, and vehicles encountered during walking, thereby enhancing their mobility and safety.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.41-53
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• 2006

In this paper, an adaptive ROI(region of interest) detection system for spatialtemporal features is proposed. It utilizes spatiotemporal features for the purpose of detecting ROI. It is assumed that motion representing temporal visual conspicuity between adjacent frames takes higher priority over spatial visual conspicuity. Because objects or regions in motion usually draw stronger attention than others in motion pictures. In case of still images visual features that constitute topographic feature maps are used as spatial features. Comparative experiments with a human subjective evaluation show that correct detection rate of visual attention region is improved by exploiting both spatial and temporal features compared to the case of exploiting either feature.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.5
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• pp.813-827
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• 2017

Surveillance cameras installed in tunnels capture the various video frames effected by dynamic and variable factors. In addition, localizing and managing the cameras in tunnel is not affordable, and quality of capturing frame is effected by time. In this paper, we introduce a new method to detect and track the vehicles in tunnel by using surveillance cameras installed in a tunnel. It is difficult to detect the video frames directly from surveillance cameras due to the motion blur effect and blurring effect on lens by dirt. In order to overcome this difficulties, two new methods such as Differential Frame/Non-Maxima Suppression (DFNMS) and Haar Cascade Detector to track cars are proposed and investigated for their feasibilities. In the study, it was shown that high precision and recall values could be achieved by the two methods, which then be capable of providing practical data and key information to an automatic accident detection system in tunnels.

• The Journal of the Korea Contents Association
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• v.6 no.4
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• pp.98-108
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• 2006

In the past, the Image processing system is independently implemented and has a limit in its application to a degree of simple display. The scope of present image processing system is diversely extended in its application owing to the development of image processing IC chips. In this paper, we implement the image processing system operated independently without PC by converting analogue image signals into digital signals. In the proposed image processing system, we extract the motion parameters from analogue image signals and generate the virtual movement to Simulator and operate Simulator by extracting motion parameters.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.474-475
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• 2018

전 세계적으로 9.11로 대표되는 자살테러, 비행기테러, 화학가스 테러 등에 의한 인명피해가 늘고 있다. 1986년 김포공항 폭발사고, 1995년 음진리교 지하철 사린가스 사건, 2001년 9.11 사건, 2003년 필리핀 공항 폭탄테러 사건 등의 큰 테러 외에도 작은 사건은 무수히 많다. 이러한 테러 사태를 미연에 방지하기 위한 지능형 영상 보안 감시 시스템이 사회적으로 연구되어왔고 도입되어 왔다. 기존의 지능형 영상 보안 시스템은 모션 디렉션 기반으로 금지구역의 침입자로 판단되는 사람을 찾는 기능 중심으로 발전해왔다. 또한 보안요원의 관찰 모니터를 통해 화면을 계속 주시하는 한계 시간의 존재와 모니터 증가에 따른 한계 시간은 더 급감하게 되는 것으로 판단되었다. 이에 본 연구를 통해 유기물 탐지의 자동화를 추구하고, 보안 요원의 감시 업무를 도와 국가 주요 시설물의 유기물 자동 탐지를 통해 테러로부터 안전하게 보호하고자 한다.