• ETRI Journal
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• v.24 no.1
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• pp.1-11
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• 2002

A video summary abstracts the gist from an entire video and also enables efficient access to the desired content. In this paper, we propose a novel method for summarizing news video based on multimodal analysis of the content. The proposed method exploits the closed caption data to locate semantically meaningful highlights in a news video and speech signals in an audio stream to align the closed caption data with the video in a time-line. Then, the detected highlights are described using MPEG-7 Summarization Description Scheme, which allows efficient browsing of the content through such functionalities as multi-level abstracts and navigation guidance. Multimodal search and retrieval are also within the proposed framework. By indexing synchronized closed caption data, the video clips are searchable by inputting a text query. Intensive experiments with prototypical systems are presented to demonstrate the validity and reliability of the proposed method in real applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1040-1057
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• 2014

In this paper, a new bit rate estimation scheme is proposed to determine the bit rate for each subclass in an MPEG-2 TS to H.264/AVC transcoder after dividing an input MPEG-2 TS sequence into several subclasses. Video format transcoding in conventional IPTV and Smart TV services is a time-consuming process since the input sequence should be fully transcoded several times with different bit-rates to decide the bit-rate suitable for a service. The proposed scheme can automatically decide the bit-rate for the transcoded video sequence in those services which can be stored on a video streaming server as small as possible without losing any subject quality loss. In the proposed scheme, an input sequence to the transcoder is sub-classified by hierarchical clustering using a parameter value extracted from each frame. The candidate frames of each subclass are used to estimate the bit rate using a statistical analysis and a mathematical model. Experimental results show that the proposed scheme reduces the bit rate by, on an average approximately 52% in low-complexity video and 6% in high-complexity video with negligible degradation in subjective quality.

• Journal of Broadcast Engineering
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• v.6 no.2
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• pp.148-159
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• 2001

This paper presents a selective duality control system to control relative picture quality among the video programs in terms of Peak Signal-to-Noise Ratio (PSNR) . The selective quality control system allows variable bit rate (VBR) for each video program to maintain the pre-determitted relative picture Quality among aggregated video programs while keeping a constant bit rate for alt programs to be transmitted over a single constant bit rate (CBR) channel. Thus is achieved by simultaneous controlling the video encoders to generate VBR video streams at the central controller. furthermore, we also suggest a buffer regulation method based on the analysis of the constraints Imposed by sender/receiver buffer sizes and the total transmission rate. Through various simulation results, it is found that the proposed quality control system guarantees that the video buffers neither overflow nor underflow and the quality control errors do not exceed 0.1 dB.

• ETRI Journal
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• v.35 no.6
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• pp.1105-1114
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• 2013

Owing to the large number of video programs available, a method for accessing preferred videos efficiently through personalized video summaries and clips is needed. The automatic recognition of user states when viewing a video is essential for extracting meaningful video segments. Although there have been many studies on emotion recognition using various user responses, electroencephalogram (EEG)-based research on preference recognition of videos is at its very early stages. This paper proposes classification models based on linear and nonlinear classifiers using EEG features of band power (BP) values and asymmetry scores for four preference classes. As a result, the quadratic-discriminant-analysis-based model using BP features achieves a classification accuracy of 97.39% (${\pm}0.73%$), and the models based on the other nonlinear classifiers using the BP features achieve an accuracy of over 96%, which is superior to that of previous work only for binary preference classification. The result proves that the proposed approach is sufficient for employment in personalized video segmentation with high accuracy and classification power.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.493-500
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• 2001

Video scene segmentation is fundamental role for content based video analysis. In this paper, we propose a new region based video scene segmentation method using continuity test for each object region which is segmented by the watershed algorithm for all frames in video data. For this purpose, we first classify video data segments into classes that are the dynamic and static sections according to the object movement rate by comparing the spatial and shape similarity of each region. And then, try to segment each sections by grouping each sections by comparing the neighbor section sections by comparing the neighbor section similarity. Because, this method uses the region which represented on object as a similarity measure, it can segment video scenes efficiently without undesirable fault alarms by illumination and partial changes.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.389-396
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• 2016

This study analyzes factors that influence use diversity or usage of mobile video services. This study conducts multiple regression analysis to draw the major factors that affect use diversity or usage of mobile video services. The major findings of this study are as follows. First, IPTV membership status, DMB watching status, and TV contents broadcasting status affect the use diversity of mobile video services. Second, TV contents broadcasting status and video streaming quality affect the usage of mobile video services. This study provides some implications that TV contents broadcasting is a core element in mobile video services. The future research is discussed.

• The Research Journal of the Costume Culture
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• v.27 no.6
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• pp.599-614
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• 2019

The aim of this study to provide basic reference data for the development of video contents used in pattern drafting education and to explore the possibility of utilizing YouTube videos in such education. Subject videos were selected using the number of views. A total of 596 videos and 28 channels were analyzed for the period July to September 2019 and the results are as follows. With regard to content, there were 27 pattern drafting items, the majority being dress, pants, skirt, blouse and sleeve drafting, although high-level content such as cowl, bustier, corset patterns were also available. Therefore, there is a high likelihood that YouTube videos could be used as educational material, especially as supplementary references to provide specific examples and easy explanations for difficult concepts or method, for students majoring in this field. However, as most videos currently focus on a few items, expanding video content to features a wider variety of clothing items at different levels is necessary. With regard to video length, it mostly ranged from 10 to 15 minutes. It is not advisable to create lengthy lecture-style videos expounding on different principles or variations in pattern drafting when developing educational video material.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.9
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• pp.746-752
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• 2012

SVC layered video is consists of a Base Layer (BL) and Enhancement Layer (EL). Without the base layer decoding, the higher EL layer can not be decoded. Therefore, successful transfer of the BL is important factor for improving the SVC video data. In this paper, we propose a network coding of layered video to improve success decoding probability with the importance order of the video data over a multi-relay system. We shows that formula analysis and experimental results of the proposed network coding scheme. In addition, we shows performance of video quality according to the number of relays.

• Journal of Broadcast Engineering
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• v.15 no.1
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• pp.144-147
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• 2010

Recently the change of content consumption trend activated the social video sharing platform and the video clip itself. There have been intensive interests and efforts to automatically abstract compact and meaningful video clips. In this paper, we propose a method which use the clustering of the bookmark data created by collective intelligence instead of using the video content analysis. The partitional clustering of points in 2-dimensional space derived from the bookmark data make it possible to abstract highlights effectively. The method is enhanced by the 1-dimensional accumulated bookmark count graph. Experiments on the real data from KBS internet service show the effectiveness of the proposed method.

• 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.