• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.225-228
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• 2001

We describe the implementation of MPEG-4 Systems for Video on Demand services. We discuss the issues in implementint MPEG-4 Systems, specially Object Description and Elementary stream management(Buffer control, Synchronization). The file-server pump the multiplexed streams to the client through the DMIF. Interaction between server and client is done with User Command(play, pause, stop, fast foward, ...). Stream data are multiplexed off-line. In advance, the file-server read multiplexed streams and pumps it to MPEG-4 terminal(client). Our system can be used in various application not only Video on Demand services, but also Internet broadcasting, remote surveillance, mobile communication, remote education, etc.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3943-3957
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• 2016

As digital evidence has a highly influential role in proving the innocence of suspects, methods for integrity verification of such digital evidence have become essential in the digital forensic field. Most surveillance camera systems are not equipped with proper built-in integrity protection functions. Because digital forgery techniques are becoming increasingly sophisticated, manually determining whether digital content has been falsified is becoming extremely difficult for investigators. Hence, systematic approaches to forensic integrity verification are essential for ascertaining truth or falsehood. We propose an integrity determination method that utilizes the structure of the video content in a Video Event Data Recorder (VEDR). The proposed method identifies the difference in frame index fields between a forged file and an original file. Experiments conducted using real VEDRs in the market and video files forged by a video editing tool demonstrate that the proposed integrity verification scheme can detect broken integrity in video content.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.9
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• pp.2328-2340
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• 1996

Until now, the transmission of data for VOD(Video on Demenad) was based on a real time modelling of video data. Markow Modulated Fluid Sources(MMFS) and Markow Modulated Poisson Sources(MMPS) are the most widely used modelling methods. But the charactersitics of the VBR(Variable Bit Rate) signal prevents modelling from actually being "real-time". Also these methods call for the use of large buffers for the abolishment of cell loss. These modelling methods are, of course, useful i case of teleconferences where a real time modelling of video traffic is inevitable, but they are insufficient in cases where the characteristic infomation of video traffic can be obtained beforehand-cases such as VOD. Video data is speial in that if one file is preprocessed all other products can simply be copied from that onepreprocessed file. This characteristic helps reduce the overhead arising from the job of drawing out characteristic information to almost zero. But still, compared to the existing real time modelling method data transmission using characteristic information succeeds in raising the efficiency of data transmission. In tis paper we will outline a method of dta transmission which use the characteristic information of each video stream, and evaluate this method through some experiments.periments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.1
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• pp.65-72
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• 2007

This paper aims to provide information to generate a statistical load model of an educational server by analyzing workload of an e-Learning sewer at Dankook University. The result of the analysis shows file size distribution, access frequency and transmission volume for each file type, access interval, changes in preference and clients access rate by networks. In particular, it had different results from previous studies about video file's size distribution and file distribution based on access frequency. This is because the characteristics of e-learning are influenced by using authoring tools for making into video file and by freeing the number of students who register for a course. The result in this paper can be used as a basic data for studies designed to improve e-learning system architecture and server performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.652-657
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• 2015

BitTorrent is an innovative protocol related to file-sharing and file-transferring, which allows users to receive pieces of files from multiple sharer on the Internet to make the pieces into complete files. In reality, however, free distribution of illegal or copyright related video data is counted for crime. Difficulty of regulation on the copyright of data on BitTorrent is caused by the fact that data is transferred with the pieces of files instead of the complete file formats. Therefore, the classification process of file formats of the digital contents should take precedence in order to restore digital contents from the pieces of files received from BitTorrent, and to check the violation of copyright. This study has suggested SVM classifier for the classification of digital files, which has the feature vector of histogram differential on the pieces of files. The suggested classifier has evaluated the performance with the division factor by applying the classifier to three different formats of video files.

• JSTS:Journal of Semiconductor Technology and Science
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• v.7 no.4
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• pp.229-234
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• 2007

In this paper, we present an efficient instruction set architecture using vector register file hardware to accelerate operation of general matrix-vector operations in DSP microprocessor. The technique enables in-situ row-access as well as column access to the register files. It can reduce the number of memory access significantly. The technique is especially useful for block-based video signal processing kernels such as FFT/IFFT, DCT/IDCT, and two-dimensional filtering. We have applied the new instruction set architecture to in-loop deblocking filter processing in H.264 decoder. Performance comparisons show that the required load/store operations for the in-loop deblocking filter can be reduced about 42%. The architecture would improve the processing speed, and code density in DSP microprocessor especially for video signal processing substantially.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.382-403
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• 2020

Steganography is the art of concealing the existence of a secret data in a non-secret digital carrier called cover media. While the image of steganography methods is extensively researched, studies on other cover files remain limited. Videos are promising research items for steganography primitives. This study presents an improved approach to video steganography. The improvement is achieved by allowing senders and receivers exchanging secret data without embedding the hidden data in the cover file as in traditional steganography methods. The method is based mainly on searching for exact matches between the secret text and the video frames RGB channel pixel values. Accordingly, a random key-dependent data is generated, and Elliptic Curve Public Key Cryptography is used. The proposed method has an unlimited embedding capacity. The results show that the improved method is secure against traditional steganography attacks since the cover file has no embedded data. Compared to other existing Steganography video systems, the proposed system shows that the method proposed is unlimited in its embedding capacity, system invisibility, and robustness. The system achieves high precision for data recovery in the receiver. The performance of the proposed method is found to be acceptable across different sizes of video files.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.114-125
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• 2002

Although there have been a lot of researches on a video abstraction algorithm, the video abstraction tool is necessary to correctly pick up some important shots in a video because the important shots might vary on the person's subjectivity. This paper proposes a video abstraction and search system for making a video abstraction automatically or manually. Proposed system has two main components, server and client. The server generates the Metadata and makes a video abstraction file. The description for video abstraction file is based on MPEG-7. Since proposed system has a function to manually correct the results of each step, the author could produce a good video abstraction easily and efficiently. The proposed system could be used to build a digital video library.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.986-1005
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• 2020

In this paper, we propose AnoVid, an automated video annotation tool based on deep neural networks, that automatically generates various meta data for each scene or shot in a long drama video containing rich elements. To this end, a novel meta data schema for drama video is designed. Based on this schema, the AnoVid video annotation tool has a total of six deep neural network models for object detection, place recognition, time zone recognition, person recognition, activity detection, and description generation. Using these models, the AnoVid can generate rich video annotation data. In addition, AnoVid provides not only the ability to automatically generate a JSON-type video annotation data file, but also provides various visualization facilities to check the video content analysis results. Through experiments using a real drama video, "Misaeing", we show the practical effectiveness and performance of the proposed video annotation tool, AnoVid.

• Journal of Platform Technology
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• v.11 no.1
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• pp.11-22
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• 2023

Various video conferencing and collaboration applications have emerged due to the global epidemic of new viral infections. In addition to real-time video conferencing, video conferencing applications provide features such as chat and file sharing on various platforms. Because various personal information is stored through functions such as chatting, file and screen sharing, these video conferencing applications are the major target of analysis from a digital forensic investigation. In the case of applications that provide cross-platform, the form of stored data is different depending on the platform. Therefore, to utilize data of video conferencing application for forensic investigation, preliminary research on artifacts stored by platform is required. In this paper, we used the video conferencing applications GoToWebinar and GoToMeeting and analyzed the artifacts generated. As a result, we list the main data from a digital forensic investigation. We identify data stored for each platform provided by GoToWebinar and GoToMeeting and organize artifacts that can estimate user behavior. Also, we classify the data that can be acquired according to the role and environment within the video conference.