• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.373-376
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• 2010

요즘 현금카드나 신용카드를 훔치고 비밀번호를 알아내 ATM(현금자동지급기)에서 현금을 인출하는 범죄가 늘고 있는데 범인들은 대부분 선글라스, 안경, 마스크, 모자 등으로 얼굴을 가리고 인출을 함으로 은행의 CCTV는 범인색출에 거의 도움이 되지 않는다. 본 논문에서의 영상처리는 모두 Java언어를 사용하였으며 피부색을 사전 추출하는 과정을 거쳐 구현된 분류기능을 이용해 얼굴의 이목구비들의 위치를 인식하도록 한다. 이는 ATM이용자가 선글라스, 안경, 마스크 등으로 얼굴을 가리면 기기에서 애초에 서비스 받는 것을 불가능 하게 하여, 범죄를 예방할 수 있게 한다. 또한 카드의 사용자 정보와 서비스를 시도했던 시간과 캡쳐 이미지를 저장해 놓음으로써 범인의 인상착의, 알리바이 등을 확인하는데 크게 도움을 주는 ATM 안면 인식 보안 시스템의 가능성을 제안하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.507-509
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• 2023

최근 딥러닝은 도로 CCTV 동영상의 교통사고 검출에 널리 사용되지만 일인칭 동영상의 교통사고 검출은 분명히 어렵다. 일인칭 동영상은 역동적이고 시야가 제한되어 있기 때문이다. 본 논문에서는 일인칭 동영상을 분석하여 교통사고를 검출하는 방법을 제시한다. 이 방법은 교통 표현 특성을 분석하는 것 외에도 의미를 이해하고 교통 장면을 인코딩한다. 프레임의 표현 특징은 각 프레임 상의 물체의 특징과 물체의 위치 관계의 공간적 숨겨진 특진을 학습함으로써 얻어진다. 그 후에 프레임 표현 특징과 교통 장면의 특징이 연결되어 GRU 실행기에 공급된다. 여러 GRU 실행기는 분석한 후 사고가 발생했는지 확인된다. 이 방법은 높은 역학과 제한된 시야 문제를 효과적으로 해결한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.111-112
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• 2023

학교, 대형 쇼핑몰, 공항 등과 같은 큰 실내 공간에서는 군중의 동선과 밀도를 파악하고 관리하는 것은 안전사고와 연관되어 있어 매우 중요하다. 와이파이 센싱은 기존에 존재하던 CCTV 카메라나 센서를 활용한 혼잡도 관리보다 효율적이고 정확한 방식으로 추정하는 데 도움이 되며, 설치 및 유지보수 측면에서도 효율적이다. 본 논문에서는 실내 환경에서 군중 수를 추정하기 위해 딥 러닝을 이용한 무선랜 신호 분석 기법을 제안한다. 송수신기가 같은 공간에 위치했던 기존 연구들과는 달리 본 논문에서는 송신기와 수신기가 서로 다른 공간에 배치된 환경에서도 무선랜 수신 신호를 통해 다른 공간의 군중 수를 정확히 예측할 수 있다는 것을 실험으로 검증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.705-708
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• 2023

다중밀집 사고를 사전에 방지하기 위해 군중 밀집도를 정확하게 파악하는 것은 중요하다. 기존 방법 중 일부는 군중 계수를 기반으로 군중 밀집도를 추정하거나 원근 왜곡이 있는 데이터를 그대로 학습한다. 이 방식은 물체의 거리에 따라 크기가 달라지는 원근 왜곡에 큰 영향을 받는다. 본 연구는 보행자 깊이 정보를 이용한 군중 밀집도 알고리즘을 제안한다. 보행자의 깊이 정보를 계산하기 위해 편차가 적은 머리 크기를 이용한다. 머리를 탐지하기 위해 OC-Sort를 학습모델로 사용한다. 탐지된 머리의 경계박스 좌표, 실제 머리 크기, 카메라 파라미터 등을 이용하여 보행자의 깊이 정보를 추정한다. 이후 깊이 정보를 기반으로 밀도 맵을 추정한다. 제안 알고리즘은 혼잡한 환경에서 객체의 위치와 밀집도를 정확하게 분석하여 군중밀집 사고를 사전에 방지하는 지능형 CCTV시스템의 기반 기술로 활용될 수 있으며, 더불어 보안 및 교통 관리 시스템의 효율성을 향상하는 데 중요한 역할을 할 것으로 기대한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.8-15
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• 2018

This article investigates intelligent security integrated platform for real-time crime response and preventive crime prevention. This study analyzed intelligent crime prevention platform elements by analyzing crime prevention system/platform research, intelligent crime prevention research, and case study of municipality integrated operation center crime prevention system. Through this, we developed a practical intelligent security platform, and suggested a linkage with existing municipalities and smart city integrated platform system considering scalability. This enables CCTV monitoring, which is used only for existing post processing, to cope with real-time crime. It is expected that it will be able to solve the incidents in golden-time by grasping the precise position of the complainant not only in the outdoor but also indoors. It is also possible to provide citizen-centered crime-prevention social safety net information sharing service by enhancing citizen participation as well as improving control efficiency. The intelligent security platform has advantages that it is easy to spread the municipality because it is developed considering existing municipal system, smart city integration platform, and linkage and expansion with other security services.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2123-2130
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• 2015

For such automatic monitoring robot or a robot cleaner that is utilized indoors, if it deviates from someone by replacement or, or of a mobile robot such as collisions with unexpected object direction or planned path, based on the planned path There is a need to come back to, it is necessary to tough self-position estimation ability of mobile robot in this, which is also associated with resolution of the kidnap problem of conventional mobile robot. In this study, the case of a mobile robot, operates indoors, you want to take advantage of the low cost of the robot. Therefore, in this paper, by using the acquisition device to an external image information such as the CCTV which is installed in a room, it acquires the environment image and take advantage of marker recognition of the mobile robot at the same time and converted it absolutely spatial coordinates it is, we are trying to solve the self-position estimation of the mobile robot in the room and kidnap problem and actual implementation methods potential field to try utilizing robotic systems. Thus, by implementing the method proposed in this study to the actual robot system, and is promoting the relevant experiment was to verify the results.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.45-55
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• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.

• Journal of KIISE:Information Networking
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• v.35 no.5
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• pp.453-463
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• 2008

The missing child problem is no more a personal problem. It became a social problem that all parents must consider. To this, this study applies USN/RFID technology integrated with GIS for the prevention of missing child. Although RFID is not designed for location sensing, but now it is regarded as a device to facilitate real time location awareness. Such advantages of RFID can be integrated with 4S(GIS/GPS/LBS/GNSS) achieving much synergy effects. In order to prevent kidnapping and missing child, it is necessary to provide a missing child preventing system using a ubiquitous computing system. Therefore, the missing child preventing system has been developed using high-tech such as RFID, GPS network, CCTV, and mobile communication. The effectiveness of the missing child prevention system can be improved through an accurate location tracking technology. This study propose and test a location sensing system using the active RFID tags. This study verifies technical applied service, and presents a system configuration model. Finally, this paper confirms missing child prevention system utilization possibility.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.655-663
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• 2017

With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.

• Progress in Medical Physics
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• v.15 no.1
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• pp.30-38
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• 2004

Purpose: To develop a whole body frame for the purpose of reducing patient motion and minimizing setup error for extra-cranial stereotactic radiotherapy, and to evaluate the repositioning setup error of a patient in the frame. Materials and Methods: The developed whole body frame is composed of a base plate, immobilizer, vacuum cushion, ruler and belts. The dimension of the base plate is 130 cm in length, 50 cm in width and 1 cm in thickness. The material used in the base plate of the frame was bakelite and the immobilizer was made of acetal. In addition, Radiopaque angio-catheter wires were engraved on the base plate for a coordinate system to determine the target localization. The measurement for radiation transmission and target localization is peformed in order to test the utilization of the frame. Also, a Matlab program analyzed the patients setup error by using the patient's setup images obtained from a CCTV camera and digital record recorder (DVR). Results: A frame that is useful for CT simulation and radiation treatment was fabricated. The frame structure was designed to minimize collisions from the changes in the rotation angle of the gantry and to maximize the transmission rate of the Incident radiation at the lateral or posterior oblique direction. The lightening belts may be used for the further reduction of the patient motion, and the belts can be adjusted so that they are not in the way of beam direction. The radiation transmission rates of this frame were measured as 95% and 96% at 10 and 21 MV, respectively. The position of a test target on the skin of a volunteer is accurately determined by CT simulation using the coordinate system in the frame. The estimated setup errors by Matlab program are shown 3.69$\pm$1.60, 2.14$\pm$0.78 mm at the lateral and central chest, and 7.11 $\pm$2.10, 6.54$\pm$2.22 mm at lateral and central abdomen, respectively. The setup error due to the lateral motion of breast is shown as 6.33$\pm$ 1.55 mm. Conclusion: The development and test of a whole body frame has proven very useful and practical in the radiosurgery for extra-cranial cancers. It may be used in determining target localization, and it can be used as a patient immobilization tool. More experimental data should be obtained in order to improve and confirm the results of the patient setup error.