• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7A
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• pp.711-723
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• 2002

A finer granular scalable (FGS) version of ISO/IEC MPEG-4 video streaming is investigated in this work with the prioritized stream delivery over loss-rate differentiated networks. Our proposed system is focused on the seamless integration of rate adaptation, prioritized packetization, and simplified differentiation for the MPEG-4 FGS video streaming. The proposed system consists of three key components: 1) rate adaptation with scalable source encoding, 2) content-aware prioritized packetization, and 3) loss-based differential forwarding. More specifically, a constant-quality rate adaptation is first achieved by optimally truncating the over-coded FGS stream based on the embedding rate-distortion (R-D) information (obtained from a piecewise linear R-D model). The rate-controlled video stream is then packetized and prioritized according to the loss impact of each packet. Prioritized packets are transmitted over the underlying network, where packets are subject to differentiated dropping and forwarding. By focusing on the end-to-end quality, we establish an effective working conditions for the proposed video streaming and the superior performance is verified by simulated MPEG-4 FGS video streaming.

• Asia pacific journal of information systems
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• v.31 no.1
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• pp.17-42
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• 2021

This study examines the adoption of subscription-based video on demand (SVOD) streaming services among consumers. Primarily, we explore the moderating effect of the two models of streaming services, standalone streaming services and bundled streaming services, on the users' adoption. We employ the Unified Theory of Acceptance and Use of Technology (UTAUT2) model in this study. We utilize the data collected from 337 Indian respondents and find that all constructs of the UTAUT2 model act as motivators of adoption. Gender, age, and experience of the respondent also play a moderating role in the adoption of streaming services. We also find that providing bundled streaming service positively moderates price-value and hedonic motivation of adoption. The study is perhaps the first of its kind that aims to understand the motivations for adoption of SVOD services, particularly in the Indian context, which has the fastest-growing base of internet users in the world.

• 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.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.33-48
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• 2020

By Digital Transformation, new technologies like ML (Machine Learning), Big Data, Cloud, VR/AR are being used to video streaming technology. We choose ML to provide optimal QoE (Quality of Experience) in various network conditions. In other words, ML helps DASH in providing non-stopping video streaming. In DASH, the source video is segmented into short duration chunks of 2-10 seconds, each of which is encoded at several different bitrate levels and resolutions. We built and compared the performances of five prototypes after applying five different machine learning algorithms to DASH. The prototype consists of a dash.js, a video processing server, web servers, data sets, and five machine learning models.

• Journal of information and communication convergence engineering
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• v.14 no.4
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• pp.240-245
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• 2016

Scalable video streaming over wireless networks has many challenges. The most significant challenge is related to packet loss. To overcome this problem, in this paper, we propose an unequal loss protection (ULP) method using a new forward error correction (FEC) mechanism for robust scalable video streaming over wireless networks. For an efficient FEC assignment considering video quality, we first introduce a simple and efficient performance metric, the layer-based recovery rate (LRR), for quantifying the unequal error propagation effects of the temporal and quality layers on the basis of packet losses. LRR is based on the unequal importance in both the temporal and the quality layers of a hierarchical scalable video coding structure. Then, the proposed ULP-LRR method assigns an appropriate number of FEC packets on the basis of the LRR to protect the video layers against packet lossy network environments. Compared with conventional ULP algorithms, the proposed ULP-LRR algorithm demonstrates a higher performance for various error-prone wireless channel statuses.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6C
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• pp.615-623
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• 2003

This paper presents effective quality-of-service renegotiating schemes for streaming video. The conventional network supporting quality-of-service generally allows a negotiation at call setup. However, it is not efficient for the video application since the compressed video traffic is statistically non-stationary. Thus, we consider the network supporting quality-of-service renegotiations during the data transmission, and study effective quality-of-service renegotiating schemes for streaming video. Simple token bucket model, whose parameters are token filling rate and token bucket size, is adopted for the video traffic model. The renegotiating time instants and the parameters are determined by analyzing the statistical information of compressed video traffic. In this paper, two renegotiating approaches, i.e. fixed renegotiating interval case and variable renegotiating interval case, are examined. Finally, the experimental results are provided to show the performance of the proposed schemes.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1053-1063
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• 2019

Recently, tile-based streaming that transmits one 360 video in several tiles, is actively being studied in order to transmit these 360 video more efficiently. In this paper, for the transmission of high-definition 360 video corresponding to user's viewport in tile-based streaming scenarios, a system of assigning the quality of tiles at each tile by applying the saliency map generated by existing network models is proposed. As a result of usage of Motion-Constrained Tile Set (MCTS) technique to encode each tile independently, the user's viewport was rendered and tested based on Salient360! dataset, streaming 360 video based on the proposed system results in gain to 23% of the user's viewport compared to using the existing high-efficiency video coding (HEVC).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4A
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• pp.421-430
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• 2006

In this paper, we propose a practical implementation of network-adaptive HD(high definition) MPEG-2 video streaming with a cross-layered channel monitoring(CLM) over the IEEE 802.11a WLAN(wireless local area network). For wireless channel monitoring, AP(access point) periodically measures the MAC(medium access control) layer transmission information and sends the monitoring information to a streaming server. This makes that the streaming server reacts more quickly as well as efficiently to the fluctuated wireless channel than that of the end-to-end monitoring(E2EM) scheme for the video adaptation. The streaming sewer dynamically performs the priority-based frame dropping to adjust the video sending rate according to the measured wireless channel condition. For this purpose, our streaming system nicely provides frame-based prioritized packetization by using a real-time stream parsing module. Various evaluation results over an IEEE 802.11a WLAM testbed are provided to verify the intended QoS adaptation capability The experimental results show that the proposed system can effectively mitigate the quality degradation of video streaming caused by the fluctuations of time-varying wireless channel condition.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.948-955
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• 2019

As interests in 360-degree VR (Virtual Reality) video services enormously grow, compression and streaming technologies for VR video data have been rapidly developed. Quality Emphasized Region (QER) based streaming scheme has been developed as a kind of viewport-adaptive 360-degree video streaming technology for maintaining immersive experience and reducing bandwidth waste. For selecting a QER corresponding to the user's gaze coordinate, QER-based streaming scheme requires the calculation of Quality Emphasis Center (QEC) distance and signaling message delivery for requesting QER switching. QEC distance calculations require high computational complexity because of repeated calculations as many times as the number of QERs. Furthermore, the signaling message interval results in a trade-off relationship between efficient bandwidth usage and flexible QER switching. In this paper, we propose an improved QER selection algorithm based on MMT protocol to solve this problem. The proposed algorithm could achieve computational complexity reduction by using preprocessed QER_ID_MAP. Also, flexible QER switching could be achieved, as well as efficient bandwidth utilization by an adaptive adjustment of the signaling interval.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.848-859
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• 2022

This paper presents a novel 360-degree video streaming system for large-scale immersive displays and its ongoing implementation. Recent VR systems aim to provide a service for a single viewer on HMD. However, the proposed 360-degree video streaming system enables multiple viewers to explore immersive contents on a large-scale immersive display. The proposed 360-degree video streaming system is being developed in 3 research phases, with the final goal of providing 6DoF. Currently, the phase 1: implementation of the 3DoF 360-degree video streaming system prototype is finished. The implemented prototype employs subpicture-based viewport-dependent streaming technique, and it achieved bit-rate saving of about 80% and decoding speed up of 543% compared to the conventional viewport-independent streaming technique. Additionally, this paper demonstrated the implemented prototype on UCSB AlloSphere, the large-scale instrument for immersive media art exhibition.