• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.510-512
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• 2015

Recently, people fear is growing because of the various crimes that may occur when you go out. The growing is interest in security systems for the protection of an individual's property. In this paper, to establish a single central server based on the home network when intruders access to city, such as image processing values obtained through the IP camera and distance values disciplined use an ultrasonic sensor the user for an attacker city that will connect to the server the surveillance system provides the information that is received and implemented.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.537-641
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• 2007

In this paper, motion analysis algorithm is presented for home surveillance of the aged who lives alone. For the first step, we acquire images from a camera. To enhance the image, we use median filtering and binarize it to reduce processing time. And then morphological operations are performed to remove small blobs and small holes. At the forth step, blobs are analysed to extracts tor foreground region. Then, motions are predicted from these images by using optical tlow technique, and the predicted motion data are refined by comparing our cardboard models so as to judge behavior pattern.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.6
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• pp.761-769
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• 2012

In this paper, we propose a low-power design strategy to minimize energy-consumption for surveillance and reconnaissance sensor networks. The sensor network consists of many different nodes with various operations such as target detection, packet relay, video monitoring, changing protocols, and etc. Each sensor node consists of sensing, computing, communication, and power components. These components are integrated on a single or multiple boards. Therefore, the power consumption of each component can be different on various operation types. First, we identified the list of components and measured power consumption for them from the first prototype nodes. Next, we focus on which components are the main sources of energy consumption. We propose many energy-efficient approaches to reduce energy consumption for each operation type.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.144-146
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• 2019

Recently, according to the rapid development of surveillance information, closed-circuit television (CCTV) has become an indispensable component in security systems. A lot of advanced technologies of encryption and compression are implementing to improve the performance and security levels of the CCTV system. Especially, 360 video CCTV streaming is promising for surveillance without blind areas. However, compared to previous systems, 360 CCTV requires large bandwidth and low latency. Therefore, it requires more efficiently effort to improve the CCTV system performance. In order to meet the demands of 360 CCTV streaming, transcoding is an essential process to enhance the current CCTV system. Moreover, encryption algorithm is also an important priority in security system. In this paper, we propose a real-time transcoding solution in combination with the ARIA and AES algorithms. Experimental results prove that the proposed method has achieved around 195% speed up transcoding compared to FFMPEG libx265 method. Furthermore, the proposed system can handle multiple transcoding sessions simultaneously at high performance for both live 360 CCTV system and existing CCTV system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.913-924
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• 2000

This paper proposes an efficient descriptor for objects motion trajectory and a video retrieval algorithm based on objects motion trajectory. The algorithm describes parameters with coefficients of 2-order polynomial for objects motion trajectory after segmentation of the object from the scene. The algorithm also identifies types, intervals, and magnitude of global motion caused by camera motion and indexes them with 6-affine parameters. This paper implements content-based video retrieval using similarity-match between indexed parameters and queried ones for objects motion trajectory. The proposed algorithm will support not only faster retrieval for general videos but efficient operation for unmanned video surveillance system.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.41-49
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• 2000

In this paper, we propose a new method of indexing and searching based on object-specific features at different semantic levels for video retrieval. A moving trajectory model is used as an indexing key for accessing the individual object in the semantic level. By tracking individual objects with segmented data, we can generate motion trajectories and set model parameters using polynomial curve fitting. The proposed searching scheme supports various types of queries including query by example, query by sketch, and query on weighting parameters for event-based video retrieval. When retrieving the interested video clip, the system returns the best matching event in the similarity order.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.1-10
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• 2023

In this paper, the design and implementation of the long-distance wireless transmission technology of high-definition video using domestic wireless communication technology for the existing wired-based CCTV surveillance system and IP camera system was evaluated for performance. The interworking test between the wireless multi-IP camera transmission terminal device and the wireless communication RF module, and the wireless multi-IP camera-based video transmission system integration interworking test confirm the module interworking suitability during video transmission.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.9
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• pp.22-30
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• 2011

Recently, the rising demand for intelligent video surveillance system leads to high-performance face recognition systems. The solution for low-resolution images acquired by a long-distance camera is required to overcome the distance limits of the existing face recognition systems. For that reason, this paper proposes a hardware design of an image resolution enhancement algorithm for real-time intelligent video surveillance systems. The algorithm is synthesizing a high-resolution face image from an input low-resolution image, with the help of a large collection of other high-resolution face images, called training set. When we checked the performance of the algorithm at 32bit RISC micro-processor, the entire operation took about 25 sec, which is inappropriate for real-time target applications. Based on the result, we implemented the hardware module and verified it using Xilinx Virtex-4 and ARM9-based embedded processor(S3C2440A). The designed hardware can complete the whole operation within 33 msec, so it can deal with 30 frames per second. We expect that the proposed hardware could be one of the solutions not only for real-time processing at the embedded environment, but also for an easy integration with existing face recognition system.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1325-1334
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• 2016

The video incident detection System is a probe for rapid detecting the walker, falling, stopped, backwards, smoke situation in tunnel. Recently, the importance is increases from the downtown double deck tunnel in great depth underground space[1], but the legal basis is weak and the vulnerable situation experimental data. So, In this paper, we introduce a long-term log data analysis information in the tunnenl video incident detection system installed and experimental results in order to verify the feasibility of apply to video incident detection system for the double deck tunnel. It is proposed a few things about derives the problem of existing video incident detection system, improvements and reflect attributes for double deck tunnel. The contents described in this paper will contribute to refine the prototype of video incident detection system will apply to future double deck multi-layer tunnels.