• 한국산학기술학회논문지
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• 제15권1호
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• pp.418-424
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• 2014

본 논문에서는 영상감시 시스템을 위한 감시영역 입력방법을 제안한다. 이동물체의 침입 여부는 감시영역과 비교를 통해 이루어지므로 이를 입력하는 방법은 영상감시의 가장 기본적인 기능이다. 기존의 방법은 각 카메라 별로 획득된 영상을 기반으로 감시영역을 설정하기 때문에 감시영역의 크기. 카메라 수, 카메라 위치 등 감시환경의 변화에 대응하기 어려운 단점이 있다. 제안하는 입력방법은 위성지도를 기반으로 감시영역 전체를 다각형으로 정의하고, 이를 각 카메라 환경으로 변환하는 접근방법을 사용한다. 이 방법의 특징은 감시환경에 독립적이라는 점이다. 다각형의 정점의 수를 n이라 하면 침입탐지 수행시간은 O(n)의 복잡도를 보인다. 제안하는 방법의 타당성을 검증하기 위해 3D 시뮬레이션을 수행하였으며, 각 카메라 수와 위치에 무관하게 입력된 감시영역을 재사용할 수 있음을 확인하였다.

• 한국측량학회지
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• 제32권2호
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• pp.153-162
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• 2014

다양한 분야에서 CCTV가 널리 활용되고 있으며, CCTV의 감시 성능을 개선하기 위한 노력들이 지속되고 있다. 그러나, 정작 감시 성능을 정량적으로 평가하는 방법은 상당히 미비하다. 이에 본 연구는 CCTV 시스템이 대상 공간을 주어진 감시 목적에 부합하게 잘 감시하는가를 정량적으로 평가하는 방법을 제안한다. 먼저 대상 공간의 특정한 위치에서 특정한 방향을 바라보는 객체가 CCTV로 얼마나 정밀하게 관측되는 가를 정량적으로 나타내는 감시 해상도를 정의한다. 정의된 감시 해상도를 대상 공간에서 관심 있는 모든 위치와 방향에 대해 계산하여 감시 목적에 따라 요구되는 최적의 해상도 이상이 성취되는 비율로써 대상 공간에 대한 감시 성능 지수를 산출한다. 제시된 방법을 적용하여 대형 건물 지하주차장에 설치된 CCTV 시스템의 감시 성능을 평가하고 가시화하여 분석하고 개선하는 사례를 기술한다. 제안된 방법은 대상 공간이 감시 목적에 맞게 효과적으로 감시되고 있는지 정량화하여 평가하고, 대상 영역을 요구 성능으로 감시하기 위한 CCTV 시스템 설계의 최적화에 기여한다.

• 로봇학회논문지
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• 제15권4호
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• pp.392-397
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• 2020

Unmanned robots are very useful for autonomous security systems. These robots navigate autonomously move in a large area for surveillance. It is very important for robots that cover such a wide area to communicate with a control systems. Therefore, the control system needs various communication methods to check the status of the robot and send/receive messages. In addition, it is necessary to provide an easy interface for the user to send security mission commands to the robot. In this paper, we propose a control system based on a variety of communication techniques to perform security by safely communicating with a number of robots in a wide area space. The proposed system designed for considering user UI, data storage and management, and shows usability by constructing it in a real environment.

• 센서학회지
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• 제24권1호
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• pp.54-61
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• 2015

In recent years, there has been increasing use of automatic surveillance and monitoring systems based on vision sensors. Humans are often the most important target in the systems, but processing human images is difficult due to the small sizes and flexible motions. Particularly, occlusion among pedestrians in camera images brings practical problems. In this paper, we propose a novel method to separate image regions of occluded pedestrians. A camera equipped with a wide angle lens is attached to the ceiling of a building corridor for sensing pedestrians with a wide field of view. The output images of the camera are processed for the human detection, tracking, identification, distortion correction, and occlusion handling. We resolve the occlusion problem adaptively depending on the angles and positions of their heads. Experimental results showed that the proposed method is more efficient and accurate compared with existing methods.

• 제어로봇시스템학회논문지
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• 제15권5호
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• pp.505-510
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• 2009

In recent years the space where a robot works has been expanding to the human space unlike traditional industrial robots that work only at fixed positions apart from humans. A human in the recent situation may be the owner of a robot or the target in a robotic application. This paper deals with the latter case; when a robot vision system is employed to monitor humans for a surveillance application, each person in a scene needs to be identified. Humans, however, often move together, and occlusions between them occur frequently. Although this problem has not been seriously tackled in relevant literature, it brings difficulty into later image analysis steps such as tracking and scene understanding. In this paper, a probabilistic neural network is employed to learn the patterns of the best dividing position along the top pixels of an image region of partly occlude people. As this method uses only shape information from an image, it is simple and can be implemented in real time.

• 대한임베디드공학회논문지
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• 제10권5호
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• pp.317-324
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• 2015

In his paper, we propose the graphic-based direction tracking system that be able to detect the current location and direction of the flight object and virtually run the pointing to the flight direction when a small UAV is located in the occlusion area behind buildings or obstacles in the moving surveillance systems. Based on the experimental results about the simulation flight path extracted from the Mission Planner we found the proposed system operates the desired flight mission effectively in tracking.

• 한국통신학회논문지
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• 제39B권4호
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• pp.228-233
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• 2014

사회 안전 서비스 제공을 위한 보안 감시 시스템이 보편화되어, 보안 감시 시스템에 대한 접근성이 확대되고, 향상되는 만큼 안정성 확보를 위한 접근제어 기법이 요구된다. ONVIF(Open Network Video Interface Forum)에서 제정하는 표준은 보안 감시용 스마트 카메라의 호환성을 목적으로 만든 표준으로, 클라이언트에게 제공될 웹서비스의 프레임워크를 정의하고 있다. 본 논문에서는 ONVIF 표준을 따르는 보안 감시 카메라 네트워크에서 안전한 시스템 접근을 위하여 웹 서비스의 정보 보호 기법을 수용하고, 웹서비스의 안전한 제공을 위한 효율적인 접근 제어 모델을 제안 한다.

• 한국멀티미디어학회논문지
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• 제18권11호
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• pp.1289-1301
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• 2015

Pedestrian detection (PD) is an essential task in various applications and sliding window-based methods utilizing HOG (Histogram of Oriented Gradients) or HOG-like descriptors have been shown to be very effective for accurate PD. However, due to exhaustive search across images, PD methods based on sliding window usually require heavy computational time. In this paper, we propose a real-time PD method for embedded visual surveillance with fixed backgrounds. The proposed PD method employs HOG descriptors as many PD methods does, but utilizes selective search so that it can save processing time significantly. The proposed selective search is guided by restricting searching to candidate regions extracted from Adaptive Gaussian Mixture Model (AGMM)-based background subtraction technique. Moreover, approximate computation of HOG descriptor and implementation in fixed-point arithmetic mode contributes to reduction of processing time further. Possible accuracy degradation due to approximate computation is compensated by applying an appropriate one among three offline trained SVM classifiers according to sizes of candidate regions. The experimental results show that the proposed PD method significantly improves processing speed without noticeable accuracy degradation compared to the original HOG-based PD and HOG with cascade SVM so that it is a suitable real-time PD implementation for embedded surveillance systems.

• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.810-816
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• 2007

A security robot system named EGIS-SR is a mobile security robot through one of the new growth engine project in robotic industries. It allows home surveillance through an autonomous mobile platform using onboard cameras and wireless security sensors. EGIS-SR has many sensors to allow autonomous navigation, hierarchical control architecture to handle lots of situations in monitoring home surveillance and mighty networks to achieve unmanned security services. EGIS-SR is tightly coupled with a networked security environment, where the information of the robot is remotely connected with the remote cockpit and patrol man. It achieved an intelligent unmanned security service. The robot is a two-wheeled mobile robot and has casters and suspension to overcome a doorsill. The dynamic motion is verified through $ADAMS^{TM}$ simulation. For the main controller, PXA270 based hardware platform based on linux kernel 2.6 is developed. In the linux platform, data handling for various sensors and the localization algorithm are performed. Also, a local path planning algorithm for object avoidance with ultrasonic sensors and localization using $StarGazer^{TM}$ is developed. Finally, for the automatic charging, a docking algorithm with infrared ray system is implemented.

• Journal of Information Processing Systems
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• 제10권1호
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• pp.1-22
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• 2014

Recent technological advances provide the opportunity to use large amounts of multimedia data from a multitude of sensors with different modalities (e.g., video, text) for the detection and characterization of criminal activity. Their integration can compensate for sensor and modality deficiencies by using data from other available sensors and modalities. However, building such an integrated system at the scale of neighborhood and cities is challenging due to the large amount of data to be considered and the need to ensure a short response time to potential criminal activity. In this paper, we present a system that enables multi-modal data collection at scale and automates the detection of events of interest for the surveillance and reconnaissance of criminal activity. The proposed system showcases novel analytical tools that fuse multimedia data streams to automatically detect and identify specific criminal events and activities. More specifically, the system detects and analyzes series of incidents (an incident is an occurrence or artifact relevant to a criminal activity extracted from a single media stream) in the spatiotemporal domain to extract events (actual instances of criminal events) while cross-referencing multimodal media streams and incidents in time and space to provide a comprehensive view to a human operator while avoiding information overload. We present several case studies that demonstrate how the proposed system can provide law enforcement personnel with forensic and real time tools to identify and track potential criminal activity.