• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.304-309
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• 2004

Recently, the needs for multimedia stream such as digital audio and video in the Internet has increased tremendously. Unlike TCP, the UDP protocol, which has been used to transmit streaming traffic thorough the Internet, does not apply any congestion control mechanism to regulate the data flow thorough the shared network And it leads to congestion collapse of the Internet and results in long-term transmission delay. To avoid any adverse effect on the current Internet functionality, a now protocol of modification or addition of some functionality to perform congestion control and to reduce huge transmission delay in transmitting of multimedia stream are in study. TCP-friendly congestion control mechanism is classified into two : one is window-based congestion control scheme using general window management functionalities, the other is rate-based congestion control scheme using TCP modeling equation. In this paper, we propose an algorithm for improving the transmitting rate on a hybrid TCP-friendly congestion control scheme combined with widow-based and late-based congestion control for multimedia stream. And we also simulate the performance of improved TEAR implementation using NS. With He simulation results, we show that the improved TEAR can provide better fairness and lower rate fluctuations than TCP.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.132-141
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• 2019

The necessity of transmitting video data over a narrow-bandwidth exists steadily despite that video service over broadband is common. In this paper, we propose a scalable video coding framework for low-resolution video transmission over a very narrow-bandwidth network by super-resolution of decoded frames of a base layer using a convolutional neural network based super resolution technique to improve the coding efficiency by using it as a prediction for the enhancement layer. In contrast to the conventional scalable high efficiency video coding (SHVC) standard, in which upscaling is performed with a fixed filter, we propose a scalable video coding framework that replaces the existing fixed up-scaling filter by using the trained convolutional neural network for super-resolution. For this, we proposed a neural network structure with skip connection and residual learning technique and trained it according to the application scenario of the video coding framework. For the application scenario where a video whose resolution is $352{\times}288$ and frame rate is 8fps is encoded at 110kbps, the quality of the proposed scalable video coding framework is higher than that of the SHVC framework.

• Journal of KIISE:Information Networking
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• v.35 no.6
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• pp.510-520
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• 2008

These days, the network convergence for utilizing heterogeneous network on mobile device is being very actively studied. However, understanding characteristics of physical network interfaces and video encoder is needed for using the network convergence technologies efficiently. Thus, this paper proposes an optimized method for streaming video data through different network paths depending on data characteristics and channel condition. Accordingly, unlike the traditional methods, this study divides scalable coded videos by layer importance, the importance of stream information, and the importance in consideration of video decoder's robustness and selectively sends the data via multiple channels. And the experimental results show over 1dB increment in PSNR. The result of this study will provide an optimized video transmission technique in the next generation network convergence environment in which mobile devices have multiple network interfaces.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2B
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• pp.334-344
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• 2010

Recently, due to the prevalence of various mobile devices and broadband wireless networks, a significant interests and demands for multimedia streaming services over the Internet have been increasing. However, it is difficult to transmit continuous multimedia stream when mobile terminals are moving. Therefore, in order to deploy mobile IPTV service in the broadband wireless network, efficient wireless resource utilization and seamless QoE (Quality of Experience) offers to the users are an important issue. In this paper, we propose a network based adaptive streaming scheme, called MARC (Mobile Adaptive Rate Control), which controls the quality of the video and rate of the video based on the status of the wireless channel. The proposed scheme uses awareness information of the wireless channel status and controls transmitting streaming video which is suitable for the wireless channel status and mobile station location, in order to provide a seamless video playback for mobile environment in addition to improving the quality of a streaming service. The proposed MARC scheme alleviates the discontinuity of video playback and allocates suitable client buffer in broadband wireless network. Simulation results demonstrate the effectiveness of our proposed scheme.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.1
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• pp.62-69
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• 2013

This paper proposes real-time video transmission system by the car-mounted cameras based on MOST Network. Existing vehicles transmit videos by connecting the car-mounted cameras in the form of analog. However, the increase in the number of car-mounted cameras leads to development of the network to connect the cameras. In this paper, DSP is applied to process MPEG 2 encoding/decoding for real-time video transmission in a short period of time. MediaLB is employed to transfer data stream between DSP and MOST network controller. During this procedure, DSP cannot transport data stream directly from MediaLB. Therefore, FPGA is used to deliver data stream transmitting MediaLB to DSP. MediaLB is designed to streamline hardware/software application development for MOST Network and to support all MOST Network data transportation methods. As seen in this paper, the test results verify that real-time video transmission using proposed system operates in a normal matter.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.31-43
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• 2022

Traditional video compression has developed so far based on hybrid compression methods through motion prediction, residual coding, and quantization. With the rapid development of technology through artificial neural networks in recent years, research on image compression and video compression based on artificial neural networks is also progressing rapidly, showing competitiveness compared to the performance of traditional video compression codecs. In this paper, a new method capable of improving the performance of such an artificial neural network-based video compression model is presented. Basically, we take the rate-distortion optimization method using the auto-encoder and entropy model adopted by the existing learned video compression model and shifts some components of the latent information that are difficult for entropy model to estimate when transmitting compressed latent representation to the decoder side from the encoder side, and finally compensates the distortion of lost information. In this way, the existing neural network based video compression framework, MFVC (Motion Free Video Compression) is improved and the BDBR (Bjøntegaard Delta-Rate) calculated based on H.264 is nearly twice the amount of bits (-27%) of MFVC (-14%). The proposed method has the advantage of being widely applicable to neural network based image or video compression technologies, not only to MFVC, but also to models using latent information and entropy model.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1103-1109
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• 2014

The latest CCTV camera are network camera in many cases. In this case when transmitting high-quality image by internet, it could be a large load on the internet because the amount of image data is very large. In this study, we propose a method which can reduce the video traffic in this case, and evaluate its performance. We used a method for transmitting and extracting a gesture information using ToF camera such as Kinect in certain circumstances. There may be restrictions on the application of the proposed method because it depends on the performance of the ToF camera. However, it can be applied efficiently to the security or safety management of a small interior space such as a home or office.

• Journal of the Korea Computer Industry Society
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• v.3 no.8
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• pp.1027-1038
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• 2002

Multimedia data services have been widely developed with the recent progression of the Internet technology. Multimedia services, especially, must guarantee Quality of Service with restricted environment resources. The abrupt increase of transmission quanta, so called burst, and the number of client that access multimedia server, with limited network bandwidth will demage the quality of service and the utilization of network resource. Smoothing techniques can reduce the burst of a variable bit rate stream by transmitting data at a series of fixed rates. In this paper, we present a new smoothing algorithm using MPEG's characteristics in transmitting stored video data with VBR. The smoothing algorithm we present will be verified with assorted existing techniques in diverse environments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.2
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• pp.124-132
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• 2017

With the growth of interest in the UAVs, the study of the UAV collision avoidance is in progress. Lidar, Video camera, laser sensor, and ultrasonic sensor may be utilized for collision avoidance of UAV. In this paper, the characteristics of MB 1230 ultrasonic sensor is analyzed through the experiment. When concurrently using multitudinous ultrasonic sensors, ultrasonic sensors do not generate correct measurement values. To solve ultrasonic sensor interference, sequentially transmitting ultrasonics signal is suggested by using 'Enable' signal input of ultrasonic sensor, so by activating each ultrasonic sensor gradually. This proposed solution is also verified by experimentation.

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.31-42
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• 2011

Smart-Phones are utilized in disaster management field because it can deliver disaster information to large population simultaneously and quickly, and provide accurate information through situation-based service using the LBS(Location Based Service). To study on the utilization of smart phone for disaster information collection and dissemination method, this study suggest a framework which connects smart phone by loading application for reporting disaster. The disaster monitoring and situation dissemination system framework using smart phone is composed of 4 parts. First, smart phone application enters image, video, voice and text information and location of the disaster. Second, the disaster report reception and situation dissemination server receives the information, save in the DB, and send through smart phone SMS. Third, store into disaster information database. Fourth, display the disaster report and management information on 2D GIS, support the decision making process in deciding whether to manage as disaster, and disaster management web service which disseminates situation.