• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.3
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• pp.63-72
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• 1999

Recent studies on the Constant Bit Rate and Variable Bit Rate transmissions have mainly focused on the frame by frame encoder rate control based on the quantization parameter. With the existing approaches it is difficult to guarantee a consistent video quality. Also, the rate control overhead is too high for the real-time video sources. In this paper, a channel rate allocation scheme based on the control period is proposed to transmit a real-time video, in which the control period is defined by a pre-specified number of frames or group of pictures. At each control period, video traffic information is collected to determine the channel rate at the next control period. The channel rate is allocated to satisfy various channel rate constraints such that the buffer occupancy at the decoder is maintained at a target level. If the allocated channel rate approaches the level at which the negotiated traffic descriptions may be violated, the encoder rate is decreased through adjusting quantization parameters in the MPEG encoder. In the experimental results, the video quality and the overflow and underflow probabilities at the buffer are compared at different control periods. Experiments show that the video quality and the utilization of network bandwidth resources can be optimized through the suitable selection of the control period.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.483-494
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• 2015

High Efficiency Video Coding (HEVC) is the most recent video codec standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The main goal of this newly introduced standard is for catering to high-resolution video in low bandwidth environments with a higher compression ratio. This paper provides a performance comparison between HEVC and H.264/AVC video compression standards in terms of objective quality, delay, and complexity in the broadcasting environment. The experimental investigation was carried out using six test sequences in the random access configuration of the HEVC test model (HM), the HEVC reference software. This was also carried out in similar configuration settings of the Joint Scalable Video Module (JSVM), the official scalable H.264/AVC reference implementation, running on a single layer mode. According to the results obtained, the HM achieves more than double the compression ratio compared to that of JSVM and delivers the same video quality at half the bitrate. Yet, the HM encodes two times slower (at most) than JSVM. Hence, it can be concluded that the application scenarios of HM and JSVM should be judiciously selected considering the availability of system resources. For instance, HM is not suitable for low delay applications, but it can be used effectively in low bandwidth environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4572-4586
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• 2019

Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) are essential network architectures for the future Internet. The advantages of MEC and ICN such as computation and storage capabilities at the edge of the network, in-network caching and named-data communication paradigm can greatly improve the quality of video streaming applications. However, the packet loss in wireless network environments still affects the video streaming performance and the existing loss recovery approaches in ICN does not exploit the capabilities of MEC. This paper proposes a Deep Learning based Loss Recovery Mechanism (DL-LRM) for video streaming over MEC based ICN. Different with existing approaches, the Forward Error Correction (FEC) packets are generated at the edge of the network, which dramatically reduces the workload of core network and backhaul. By monitoring network states, our proposed DL-LRM controls the FEC request rate by deep reinforcement learning algorithm. Considering the characteristics of video streaming and MEC, in this paper we develop content caching detection and fast retransmission algorithm to effectively utilize resources of MEC. Experimental results demonstrate that the DL-LRM is able to adaptively adjust and control the FEC request rate and achieve better video quality than the existing approaches.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1249-1252
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• 2022

In this paper, we propose a conceptual framework that identifies video frames in motion containing the movement of people and vehicles in traffic videos. The automatic selection of video frames in motion is an important topic in security and surveillance video because the number of videos to be monitored simultaneously is simply too large due to limited human resources. The conventional method to identify the areas in motion is to compute the differences over consecutive video frames, which has been costly because of its high computational complexity. In this paper, we reduced the overall complexity by examining only the keyframes (or I-frames). The basic assumption is that the time period between I-frames is rather shorter (e.g., 1/10 ~ 3 secs) than the usual length of objects in motion in video (i.e., pedestrian walking, automobile passing, etc.). The proposed method estimates the possibility of videos containing motion between I-frames by evaluating the difference of consecutive I-frames with the long-time statistics of the previously decoded I-frames of the same video. The experimental results showed that the proposed method showed more than 80% accuracy in short surveillance videos obtained from different locations while keeping the computational complexity as low as 20 % compared to the HM decoder.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2101-2121
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• 2020

The rapid growth of instructional videos repositories and their widespread use as a tool to support education have raised the need of studies to assess the quality of those educational resources and their impact on the quality of learning process that depends on them. Khan Academy (KA) repository is one of the prominent educational videos' repositories. It is famous and widely used by different types of learners, students and teachers. To better understand its characteristics and the impact of such repositories on education, we gathered a huge amount of KA data using its API and different web scraping techniques, then we analyzed them. This paper reports the first quantitative and descriptive analysis of Khan Academy repository (KA repository) of open video lessons. First, we described the structure of repository. Then, we demonstrated some analyses highlighting content-based growth and evolution. Those descriptive analyses spotted the main important findings in KA repository. Finally, we focused on users' interactions with video lessons. Those interactions consisted of questions and answers posted on videos. We developed interaction profiles for those videos based on the number of users' interactions. We conducted regression analysis and statistical tests to mine the relation between those profiles and some quality related proposed metrics. The results of analysis showed that all interaction profiles are highly affected by video length and reuse rate in different subjects. We believe that our study demonstrated in this paper provides valuable information in understanding the logic and the learning mechanism inside learning repositories, which can have major impacts on the education field in general, and particularly on the informal learning process and the instructional design process. This study can be considered as one of the first quantitative studies to shed the light on Khan Academy as an open educational resources (OER) repository. The results presented in this paper are crucial in understanding KA videos repository, its characteristics and its impact on education.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.203-206
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• 2001

This Paper suggests real-time video streaming method by using DCT-based scalability, and evaluates and analyzes the function. It is similar to using lowpass filter. That is, as following figure, this method is to split the encoded data in splitter and transmit it, and to decode the data according to the situation. This method can be applied to any video CODEC which is based on DCT. Therefore, this thesis suggests easy video streaming method by using DCT-based scalability, and shows the result of experiment. By using suggested scalability, calculations are reduced, and spacial scalability is realized. Moreover, the objective data which meet user's need according to the network condition and choose the appropriate scalability according to the capability of terming can be extracted. And it is possible to apply any resources according to the specificity of image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1502-1506
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• 2016

HEVC (High Efficiency Video Coding) is a recently proposed video compression standard that has a two times greater coding efficiency than previous video compression standards. The key factors of high compression performance and increasement of computational complexity are the various types of block partitions and modes of intra prediction in HEVC. This paper presents an intra prediction hardware architecture for HEVC utilizing pipelining and interleaving techniques to increase the efficiency and performance while reducing the requirement for hardware resources.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.327-332
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• 2015

NCS are the contents such as knowledge, technology, and culture demanded for performing the duties in the industrial field systemized by a nation classified with industrial divisions and levels. It is an ability standardized in the national level necessary for performing duties of industrial field successfully. Now, the society structure, due to abrupt change and development, has to secure core ability demanded to human resources in common, irrespective of kinds and positions, and lays an emphasis on vocational basis ability to softly cope with the accelerating change of labor market. This dissertation, on the basis of NCS-based vocational education curriculum, focuses on information ability, computer use ability(information management ability), one of vocational core competency used for the duties related at the department of video & broadcasting to develop learning module. In addition, this dissertation researches learning results such as satisfaction and accomplishment over learning on the object of the students who took the education.

• ETRI Journal
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• v.31 no.3
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• pp.333-335
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• 2009

To match the requirements of heterogeneous mobile devices, video objects may be transcoded, which requires considerable CPU resources. Alternatively, multiple versions of the same video may be stored on servers, but this requires a lot of disk space. We formulate the trade-off between the versions that are stored on disk and the need for transcoding. We propose an optimal solution to this formulation based on dynamic programming. Experiments show that our scheme allows up to 68% more clients to be admitted than conventional schemes when a reasonable amount of storage is available.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2A
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• pp.146-156
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• 2002

This paper presents an adaptive H.263+ rate control algorithm for streaming video applications under the networks supporting bandwidth renegotiation, which can communicate with end-users to accommodate their time-varying bandwidth requests during the data transmission. That is, the requests of end-users can be supported adaptively according to the availability of the network resources, and thus the overall network utilization can be improved simultaneously. They are especially suitable for the transmission of non-stationary video traffics. The proposed rate control algorithm communicates with the network to renegotiate the required bandwidth fort the underlying video which are measured based on the motion change information, and choose their control strategies according to the renegotiation results. Unlike most conventional algorithms that control only the spatial quality by adjusting quantization parameters, the proposed algorithm treats both the spatial and temporal qualities at the same time to enhance human visual perceptual quality. Experimental results are provided to demonstrate that the proposed rate control algorithm can achieve superior performance to the conventional ones with low computational complexity under the networks supporting bandwidth renegotiation.