• The Journal of Information Systems
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• v.32 no.2
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• pp.87-108
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• 2023

Purpose The main purpose of this study is to improve fake news detection performance by using video information to overcome the limitations of extant text- and image-oriented studies that do not reflect the latest news consumption trend. Design/methodology/approach This study collected video clips and related information including news scripts, speakers' facial expression, and video metadata from YouTube to develop fake news detection model. Based on the collected data, seven combinations of related information (i.e. scripts, video metadata, facial expression, scripts and video metadata, scripts and facial expression, and scripts, video metadata, and facial expression) were used as an input for taining and evaluation. The input data was analyzed using six models such as support vector machine and deep neural network. The area under the curve(AUC) was used to evaluate the performance of classification model. Findings The results showed that the ACU and accuracy values of three features combination (scripts, video metadata, and facial expression) were the highest in logistic regression, naïve bayes, and deep neural network models. This result implied that the fake news detection could be improved by using video information(video metadata and facial expression). Sample size of this study was relatively small. The generalizablity of the results would be enhanced with a larger sample size.

• Journal of KIISE:Databases
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• v.29 no.3
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• pp.168-179
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• 2002

In this paper, we investigate video representation techniques that are the foundational work for the subsequent video processing such as video storage and retrieval. A video data set if a collection of video clips, each of which is a sequence of video frames and is represented by a multidimensional data sequence (MDS). An MDS is partitioned into video segments considering temporal relationship among frames, and then similar segments of the clip are grouped into video clusters. Thus, the video clip is represented by a small number of video clusters. The video segmentation and clustering algorithm, VDCluster, proposed in this paper guarantee clustering quality to south an extent that satisfies predefined conditions. The experiments show that our algorithm performs very effectively with respect to various video data sets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.929-946
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• 2022

Free viewpoint video (FVV) service is an immersive media service that allows a user to watch it from a desired location or viewpoint. It is composed of various forms according to the direction of the viewpoint of the provided video, and includes zoom in/out in the service. As consumers' demand for active watching is increasing, the importance of FVV services is expected to grow gradually. However, additional considerations are needed to seamlessly stream FVV service. FVV includes a plurality of videos, video changes may occur frequently due to movement of the viewpoint. Frequent occurrence of video switching or re-request another video can cause service delay and it also can lower user's quality of service (QoS). In this case, we assumed that if a video showing an object that the user wants to watch is selected and provided, it is highly likely to meet the needs of the viewer. In particular, it is important to provide an object-oriented FVV service when zooming in. When video zooming in in the usual way, it cannot be guaranteed to zoom in around the object. Zoom function does not consider about video viewing. It only considers the viewing screen size and it crop the video view as fixed screen location. To solve this problem, we propose a zoom in/out method of object-centered dynamic adaptive streaming of FVV in this paper. Through the method proposed in this paper, users can enjoy the optimal video service because they are provided with the desired object-based video.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.619-622
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• 2000

In this paper, we propose a method for generating graphic objects having realistic shadows inserted into video sequence for the enhanced augmented reality. Our purpose is to extend the work of [1], which is applicable to the case of a static camera, to video sequence. However, in case of video, there are a few challenging problems, including the camera calibration problem over video sequence, false shadows occurring when the video camera moves and so on. We solve these problems using the convenient calibration technique of [2] and the information from video sequence . We present the experimental results on real video sequences.

• ETRI Journal
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• v.27 no.6
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• pp.806-809
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• 2005

The main goal of this research is automatic video analysis using a face recognition technique. In this paper, an automatic video management system is introduced with a variety of functions enabled, such as index, edit, summarize, and retrieve multimedia data. The automatic management tool utilizes MPEG-7 visual descriptors to generate a video index for creating a summary. The resulting index generates a preview of a movie, and allows non-linear access with thumbnails. In addition, the index supports the searching of shots similar to a desired one within saved video sequences. Moreover, a face recognition technique is utilized to personalbased video summarization and indexing in stored video data.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.355-358
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• 2012

Although quality metrics for 2D video quality assessment have been proposed, the quality models on stereoscopic video have not been widely studied. In this paper, a new objective video quality metric for s tereoscopic video is proposed. The proposed algorithm consider three factors to evaluate stereoscopic video quality: blocking artifact, blurring artifact, and the difference between left and right view of stereoscopic vide o. The results show that the proposed algorithm has a higher correlation with DMOS than the others.

• Journal of Communications and Networks
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• v.6 no.4
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• pp.387-396
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• 2004

One of the main problems associated with MANETs is that mobility and the associated route discovery and maintenance procedures of reactive routing protocols cause severe interruptions on real-time video streams. Some of these interruptions are too large to be concealed using any sort of video technology, resulting in communications breaks unpleasant for the final end user. We present a solution for enhanced video transmission that increases route stability by using an improved route discovery process based on the DSR routing protocol, along with traffic splitting algorithms and a preventive route discovery mechanism. We also present some video adaptative mechanisms that improve the overall performance of multipath routing in terms of video data replication and video packet splitting strategies. Combining our proposals, we achieve up to 97% less interruptions on communication with high mobility and over 1.2 dB of improvements in terms of video distortion.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.127-130
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• 2007

The increased availability of portable, low-cost, high resolution video devices has resulted in a rapid growth of the applications for video sequences. These video devices can be mounted in handhold unit, mobile unit and airborne platforms like maned or unmaned helicopter, plane, airship, etc. A core technique in use of video sequences is to align neighborhood video frames to each other or to reference images. For video sequences registration, we extracted interested points from aerial video sequences using Harris, $F{\square}rstner$, and KLT operators and implemented image matching using these points. As the result, we analysed image matching results for each operators and evaluated accuracy of aerial video registration.

• ETRI Journal
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• v.32 no.6
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• pp.863-870
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• 2010

In recent years, the development of multimedia devices has meant that a wider multimedia streaming service can be supported, and there are now many ways in which TV channels can communicate with different terminals. Generally, scalable video streaming is known to provide more efficient channel capacity than simulcast video streaming. Simulcast video streaming requires a large network bandwidth for all resolutions, but scalable video streaming needs only one flow for all resolutions. In previous research, scalable video streaming has been compared with simulcast video streaming for network channel capacity, in two user simulation environments. The simulation results show that the channel capacity of SVC is 16% to 20% smaller than AVC, but scalable video streaming is not efficient because of the limit of the present network framework. In this paper, we propose a new network framework with an SVC extractor. The proposed network framework shows a channel capacity 50% (maximum) lower than that found in previous research studies.

• Electronics and Telecommunications Trends
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• v.32 no.5
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• pp.20-29
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• 2017

In this paper, a video conferencing system, which has been attracting significant attention as an immersive telepresence service owing to the recent emergence of 5G networks, is described. We propose a service platform for Giga Media based video conferencing for 5G convergence services. The video conferencing service consists of a traditional structure that provides information exchange through the transmission of video and voice of remote participants using a Multipoint Control Unit (MCU), a browser-based video conferencing based on WebRTC, a multi-view point video conferencing, and holographic telepresence centered on mixed reality. The paper introduces the trends and detailed structures of various technologies used in the video conferencing system, and compares the video conferencing system technologies and video conferencing service characteristics for the integrated Giga Media platform.