• ETRI Journal
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• v.43 no.3
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• pp.447-458
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• 2021

The quality of experience (QoE) of video streaming is degraded by playback interruptions, which can be mitigated by the playout buffers of end users. To analyze the impact of playout buffer dynamics on the QoE of wireless adaptive hypertext transfer protocol (HTTP) progressive video, we model the playout buffer as a G/D/1 queue with an arbitrary packet arrival rate and deterministic service time. Because all video packets within a block must be available in the playout buffer before that block is decoded, playback interruption can occur even when the playout buffer is non-empty. We analyze the queue length evolution of the playout buffer using diffusion approximation. Closed-form expressions for user-perceived video quality are derived in terms of the buffering delay, playback duration, and interruption probability for an infinite buffer size, the packet loss probability and re-buffering probability for a finite buffer size. Simulation results verify our theoretical analysis and reveal that the impact of playout buffer dynamics on QoE is content dependent, which can contribute to the design of QoE-driven wireless adaptive HTTP progressive video management.

• 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.

• The Journal of Korean Physical Therapy
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• v.33 no.1
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• pp.16-20
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• 2021

Purpose: This study examined the effects of the type of video contents used for action observations on the ability to control posture. Methods: The participants were 48 healthy adults. The two hands of the participants were crossed on both shoulders, and the other foot was placed in a straight line in front of the target to allow them to watch a video of the monitor. The videos were presented in random order with three video contents (natural, stable balance posture, and unstable balance posture) consisting of 30 seconds each. A 15-second resting time was given between each video. During action observation using various video content forms, the posture control ability was measured using a TekScan MetScan^® system. Results: The results revealed statistically significant differences in the area of movement and the distance by COP and distance by the type of action-observation videos, and the distance by the anteroposterior and mediolateral sides (p<0.05). The stable balance posture and unstable balance posture video showed significant differences in the distance by the COP, anteroposterior, and mediolateral distance. (p<0.05) Conclusion: This study suggests that choosing the contents of the videos is important during action-observation training, and action-observation training can help improve postural control.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.628-639
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• 2022

Starting from the content types of video advertisements produced by social media users, this paper conducts a comparative study on the information and entertainment video advertising effects of the same product, to help video producers achieve better advertising effects when facing different products. Experimental results show that. In Garment, the information is higher than that of entertainment in terms of advertising cognition. In terms of advertising attitude and purchase intention, the entertainment is higher than that of information; in food, the entertainment is higher than that of information in terms of advertising cognition, advertising attitude, and purchase intention; in household items, the entertainment is higher than that of information; in terms of advertising cognition and purchase intention, the information is higher than that of entertainment; in terms of advertising attitude, the entertainment is higher than that of information; in cosmetics, the information is higher than that of entertainment in terms of advertising cognition; in terms of advertising attitude and purchase intention, the entertainment is higher than that of the information; in digital accessories, the information is higher than that of the entertainment in terms of advertising cognition, advertising attitude and purchase intention.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.1-13
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• 2020

In order to understand the recommendation algorithm applied to the online video platform, this study examines the relationship between the content characteristics of K-pop music videos and related videos recommended for playback on YouTube, and analyses which videos are recommended as related videos through network analysis. As a result, the more liked videos, the higher recommendation ranking and most of the videos belonging to the same channel or produced by the same agency were recommended as related videos. As a result of the network analysis of the related video, the network of K-pop music video is strongly formed, and the BTS music video is highly centralized in the network analysis of the related video. These results suggest that the network between K-pops is strong, so when you enter K-pop as a search query and watch videos, you can enjoy K-pop continuously. But when watching other genres of video, K-pop may not be recommended as a related video.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8649-8653
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• 2015

A number of video indexing and retrieval algorithms have been proposed to manage large video databases efficiently. The video similarity measure is one of most important technical factor for video content management system. In this paper, we propose the luminance characteristics model to measure the video similarity efficiently. Most algorithms for video indexing have been commonly used histograms, edges, or motion features, whereas in this paper, the proposed algorithm is employed an efficient similarity measure using the luminance projection. To index the video sequences effectively and to reduce the computational complexity, we calculate video similarity using the key frames extracted by the cumulative measure, and compare the set of key frames using the modified Hausdorff distance. Experimental results show that the proposed luminance projection model yields the remarkable improved accuracy and performance than the conventional algorithm such as the histogram comparison method, with the low computational complexity.

• Journal of Broadcast Engineering
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• v.11 no.1 s.30
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• pp.28-41
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• 2006

Due to the rapid development of multimedia appliances, the increasing amount of multimedia data enforces the development of automatic video analysis techniques. In this paper, a method of ToC generation is proposed for educational video contents. The proposed method consists of two parts: scene segmentation followed by scene annotation. First, video sequence is divided into scenes by the proposed scene segmentation algorithm utilizing the characteristics of educational video. Then each shot in the scene is annotated in terms of scene type, existence of enclosed caption and main speaker of the shot. The ToC generated by the proposed method represents the structure of a video by the hierarchy of scenes and shots and gives description of each scene and shot by extracted features. Hence the generated ToC can help users to perceive the content of a video at a glance and. to access a desired position of a video easily. Also, the generated ToC automatically by the system can be further edited manually for the refinement to effectively reduce the required time achieving more detailed description of the video content. The experimental result showed that the proposed method can generate ToC for educational video with high accuracy.

• Journal of KIISE:Software and Applications
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• v.35 no.4
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• pp.207-218
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• 2008

With the growth of the Internet, multimedia streaming becomes an important means to deliver video contents over the Internet and the amount of the streaming multimedia contents is also getting increased. However, it becomes difficult to guarantee the quality of service in real-time over the IP network environment with instantaneously varying bandwidth. In this paper, we propose an optimal adaptation framework for streaming contents over the Internet in the sense that the perceptual quality of the multi-angie content with multiple visual objects is maximized given the constraints such as available bandwidth and transcoding cost. In the multi-angle video service framework, the user can select his/her preferred alternate views among the given multiple video streams captured at different view angles for a same event. This enhanced experience often entails streaming problems in real-time over the network, such as instantaneous bandwidth changes in the Internet. In order to cope with this problem, we assume that multi-angle video contents are encoded at different bitrates and the appropriate video streams are then selected or transcoded for delivery to meet such bandwidth constraints. For the user selective consumption of the various bitstreams in the multi-angle video service, the bitstream in each angle can be encoded in various bitrate, and the user can select a sub-bitrstream in the given bitrstreams or transcode the corresponding content in order to deliver the optimally adapted video contents to the instantaneously changing network condition. Therefore, we define the transcoding cost which means the time taken for transcoding the video stream and formulate a unified optimization framework which maximizes the perceptual quality of the multiple video objects in the given constraints such as the transcoding cost and the network bandwidth. Finally, we present plenty of the experimental results to show the effectiveness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1776-1785
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• 2015

Content Centric Network (CCN) has been introduced as a new paradigm due to a shift of users's perspective of using Internet from host-centric to content-centric. On the other hand, a demand for video streaming has been increasing. Thus, Adaptive streaming has been introduced and researched for achieving higher user's satisfaction. If an architecture of Internet is replaced with CCN architecture, it is necessary to consider adaptive video streaming in CCN according to the demand of users. However, if the same rate decision algorithm used in Internet is deployed in CCN, there are a limitation of utilizing content store (CS) in CCN router and a problem of reflecting dynamic requirements. Therefore, this paper presents a framework adequate to CCN protocol and cache utilization, adapting content naming method of exploiting regular expression to the rate decision algorithm of the existing adaptive streaming. In addition, it also improves the quality of video streaming and verifies the performance through dynamic expression strategies and selection algorithm of the strategies.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.35-38
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• 2000

The method of Content-based Triangular Mesh Image representation in moving pictures makes better performance in prediction error ratio and visual efficiency than that of classical block matching. Specially if background and objects can be separated from image, the objects are designed by Irregular mesh. In this case this irregular mesh design has an advantage of increasing video coding efficiency. This paper presents the techniques of mesh generation, motion estimation using these mesh, uses image warping transform such as Affine transform for image reconstruction, and evaluates the content based mesh design through computer simulation.