• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2170-2190
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• 2012

There are nowadays strong demands for intelligent surveillance systems, which can infer or understand more complex behavior. The application of crowd density estimation methods could lead to a better understanding of crowd behavior, improved design of the built environment, and increased pedestrian safety. In this paper, we propose a new crowd density estimation method, which aims at estimating not only a moving crowd, but also a stationary crowd, using images captured from surveillance cameras situated in various public locations. The crowd density of the moving people is measured, based on the moving area during a specified time period. The moving area is defined as the area where the magnitude of the accumulated optical flow exceeds a predefined threshold. In contrast, the stationary crowd density is estimated from the coarseness of textures, under the assumption that each person can be regarded as a textural unit. A multilayer neural network is designed, to classify crowd density levels into 5 classes. Finally, the proposed method is experimented with PETS 2009 and the platform of Gangnam subway station image sequences.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.394-406
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• 2023

In this study, a real-time surveillance system using Internet of Things technology is proposed for vaccine cold chains. This system fully visualizes vaccine transport and storage. It comprises a 4G gateway module, lowpower and low-cost wireless temperature and humidity collection module (WTHCM), cloud service software platform, and phone app. The WTHCM is installed in freezers or truck-mounted cold chain cabinets to collect the temperature and humidity information of the vaccine storage environment. It then transmits the collected data to a gateway module in the radiofrequency_physical layer (RF_PHY). The RF_PHY is an interface for calling the bottom 2.4-GHz transceiver, which can realize a more flexible communication mode. The gateway module can simultaneously receive data from multiple acquisition terminals, process the received data depending on the protocol, and transmit the collated data to the cloud server platform via 4G or Wi-Fi. The cloud server platform primarily provides data storage, chart views, short-message warnings, and other functions. The phone app is designed to help users view and print temperature and humidity data concerning the transportation and storage of vaccines anytime and anywhere. Thus, this system provides a new vaccine management model for ensuring the safety and reliability of vaccines to a greater extent.

• 한국산업정보학회논문지
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• 제17권4호
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• pp.51-59
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• 2012

최근 보안 감시 분야에서 영상처리를 이용한 객체 추적에 관한 연구가 활발히 이루어지고 있다. 기존 여러 대의 카메라를 이용한 보안 감시 시스템은 각각 독립적으로 운영되었다. 따라서 추적 객체가 다른 카메라의 감시영역으로 이동 시 계속해서 추적이 어려웠다. 이 문제를 해결하기 위해 본 논문은 다중 카메라에서 객체의 이동방향에 따라 자동으로 카메라의 제어권을 변경하는 방법을 제안한다. 제안방법은 객체를 검출하고 객체의 색상 정보와 방향 정보로 객체를 추적한다. 색상 정보는 hue를 이용하고 방향 정보는 광류를 이용하여 획득한다. 이때 광류는 전체 영상이 아닌 객체가 검출된 영역에만 적용하여 계산량을 줄여 실시간 추적이 가능하게 한다. 또한, 자동으로 객체를 추적함으로써 기존 카메라를 이용한 보안 감시 시스템의 불편함을 해결할 수 있다.

• 방송공학회논문지
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• 제24권5호
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• pp.802-812
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• 2019

최근 무인 비행체의 활용이 증가하면서 소형 드론의 활용 역시 크게 증가하고 있다. 이러한 시장의 성장으로 드론의 악용 가능성이 높아짐에 따라 드론을 적절히 통제하기 위한 감시 시스템의 필요성이 제기되고 있다. 또한 고정 카메라를 사용한 감시 시스템은 범위가 제한적이기 때문에 PTZ(Pan-Tilt-Zoom) 카메라 등에 적용 가능한 동적 카메라 환경에서의 객체 추적 연구가 필요하며, 실시간 추적을 위해 최적화된 객체 추적 연구가 필요하다. 효과적인 추적을 위해 대상 객체의 특징을 배경 환경에 맞추어 정의하거나 객체의 특징 정보를 효과적으로 추출해야 한다. 본 논문에서는 소형 드론 추적을 위해 옵티컬 플로우를 사용한 객체 추적 방법과 추적 실패로부터 재추적을 수행하기 위한 옵티컬 플로우와 칼만 필터를 결합한 방법을 소개한다. 본 논문에서는 추적 결과 비교를 위해 최소 12pixels에서 최대 56337pixels의 표적 크기에 대한 실험 결과를 보인다. 제안 방법은 기존 추적 방법과 비교하여 평균 175%의 정밀도 향상과 평균 143%의 검출률 향상 결과를 보였으며, 최소 12pixels의 표적에 대해서도 추적하는 결과를 보였다.

• 전기학회논문지
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• 제64권7호
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• pp.1047-1055
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• 2015

We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Current Optics and Photonics
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• 제7권2호
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• pp.200-206
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• 2023

Near-infrared (NIR) sensing technology using CMOS image sensors is used in many applications, including automobiles, biological inspection, surveillance, and mobile devices. An intuitive way to improve NIR sensitivity is to thicken the light absorption layer (silicon). However, thickened silicon lacks NIR sensitivity and has other disadvantages, such as diminished optical performance (e.g. crosstalk) and difficulty in processing. In this paper, a pixel structure for NIR sensing using a stacked CMOS image sensor is introduced. There are two photodetection layers, a conventional layer and a bottom photodiode, in the stacked CMOS image sensor. The bottom photodiode is used as the NIR absorption layer. Therefore, the suggested pixel structure does not change the thickness of the conventional photodiode. To verify the suggested pixel structure, sensitivity was simulated using an optical simulator. As a result, the sensitivity was improved by a maximum of 130% and 160% at wavelengths of 850 nm and 940 nm, respectively, with a pixel size of 1.2 ㎛. Therefore, the proposed pixel structure is useful for NIR sensing without thickening the silicon.

• 한국전자파학회논문지
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• 제29권3호
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• pp.214-224
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• 2018

지속적인 우주개발은 인공위성의 지구 추락, 우주잔해물과 우주선 간의 충돌 등 우주위험의 발생 가능성을 크게 증가 시킨다. 국내에서는 이러한 우주위험을 감시하기 위한 광학감시체계 구축은 진행하였으나, 독자적인 상시 우주감시 정보 획득 능력을 갖는 우주감시 레이다기술에 대해서는 확보가 필요한 실정이다. 본 논문에서는 재진입하는 우주물체의 추락 위험 및 저궤도 자국 위성의 충돌 위험에 대응하기 위한 우주감시 임무 분석 및 레이다 요구사항 도출을 통해, 우주물체의 탐지 및 추적을 위한 L-band 위상배열레이다 시스템을 제안한다. 우주감시 임무 분석 및 미국, 유럽 등 해외 선진 시스템의 사례 분석을 바탕으로 레이다 고려사항을 정의하고 레이다를 설계하였으며, 지름 10 cm 우주 파편에 대해 최대탐지거리 1,576 km를 가질 뿐, 아니라 탐지 범위 분석을 통해 국내 운용 중인 인공위성에 대해 우주감시 임무 수행이 가능함을 확인하였다.

• 한국대기환경학회지
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• 제34권5호
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• pp.735-747
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we propose to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collect a new video dataset and propose a procedure to calculate refined rainfall depth from the original meteorological data. We also propose to utilize the differential frame as well as the optical flow image for better recognition of rainfall depth. Under the Temporal Segment Networks framework, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. The final model is able to achieve high performance in the single-location low sensitivity classification task and reasonable accuracy in the higher sensitivity classification task for both the single-location and the multi-location case.

• Current Optics and Photonics
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• 제7권5호
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• pp.545-556
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• 2023

This paper introduces volume-sharing multi-aperture imaging (VMAI), a potential approach proposed for volume reduction in space-borne imagers, with the aim of achieving high-resolution ground spatial imagery using deep learning methods, with reduced volume compared to conventional approaches. As an intermediate step in the VMAI payload development, we present a phase-1 design targeting a 1-meter ground sampling distance (GSD) at 500 km altitude. Although its optical imaging capability does not surpass conventional approaches, it remains attractive for specific applications on small satellite platforms, particularly surveillance missions. The design integrates one wide-field and three narrow-field cameras with volume sharing and no optical interference. Capturing independent images from the four cameras, the payload emulates a large circular aperture to address diffraction and synthesizes high-resolution images using deep learning. Computational simulations validated the VMAI approach, while addressing challenges like lower signal-to-noise (SNR) values resulting from aperture segmentation. Future work will focus on further reducing the volume and refining SNR management.

• 디지털산업정보학회논문지
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• 제6권2호
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• pp.119-127
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• 2010

In this paper, we propose a new automatic surveillance tracking system that can extract the target from the complex background and foreground noises by using the image-based SAD algorithm and control the servo motor of cameras by using kanatani algorithm. From the experimental results the proposed stereo tracking system is found to track the target adaptively under the circumstance of complex and changing background noises and the possibility of real-time implementation of the proposed system by using the optical system is also suggested.