• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.841-851
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• 2013

The infectious information hiding system(IIHS) is proposed for secure distribution of high quality video contents by applying optimized watermark embedding and detection algorithms to video codecs. And the watermark as infectious information is transmitted while target video is displayed or edited by codecs. This paper proposes a fast and effective reversible watermarking and infectious information generation for IIHS. Our reversible watermarking scheme enables video decoder to control video quality and watermark strength actively for by adding control code and expiration date with the watermark. Also, we designed our scheme with low computational complexity to satisfy it's real-time processing in a video codec, and to prevent time or frame delay during watermark detection and video restoration, we embedded one watermark and one side information within a macro-block. Experimental results verify that our scheme satisfy real-time watermark embedding and detection and watermark error is 0% after reversible watermark detection. Finally, we conform that the quality of restored video contens is almost same with compressed video without watermarking algorithm.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2031-2041
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• 1999

In this paper, we present the HVIS (Hybrid Video Information System) which bolsters up meaning retrieval of all the various users by integrating feature-based retrieval and annotation-based retrieval of unformatted formed and massive video data. HVIS divides a set of video into video document, sequence, scene and object to model the metadata and suggests the Two layered Hybrid Object-oriented Metadata Model(THOMM) which is composed of raw-data layer for physical video stream, metadata layer to support annotation-based retrieval, content-based retrieval, and similarity retrieval. Grounded on this model, we presents the video query language which make the annotation-based query, content-based query and similar query possible and Video Query Processor to process the query and query processing algorithm. Specially, We present the similarity expression to appear degree of similarity which considers interesting of user. The proposed system is implemented with Visual C++, ActiveX and ORACLE.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.7
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• pp.398-400
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• 2014

In this letter, we propose a cross-layer technique jointly considering modulation coding schemes (MCSs) of medium access control (MAC) layer, source significance information (SSI) and error concealment unit of application (APP) layer, and channel quality information (CQI) of physical (PHY) layer. We demonstrate the improved video quality by the proposed technique when H.264 videos are streamed over Rayleigh fading wireless channels.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.3
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• pp.103-109
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• 2011

With the growing popularity of digital video applications, those areas of the efficient transmit, storage management, and search technology for video data are emerging as an important core technology. To be an effective video indexing system, users need to be able to find the video segments that they want. Unfortunately, video data is difficult to manage because of its unstructured data type and large volume with linear forms. This paper proposes a shot verification using visual rhythm and video retrieval system. The shot verification is designed to detect a segment from video easily and quickly, known as shot boundaries, just by changing the visual rhythm without playing the image. Therefore, this can decrease the false detected shots and generate the unidentified shots and key frames. The retrieval system is constructed in terms of visual descriptor from the list of MPEG-7. The effectiveness of the proposed shot verification process and video retrieval system is demonstrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1C
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• pp.124-130
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• 2008

We present in this paper a method of digital watermarking for video data based on the discrete wavelet transform. In the proposed method, a watermark signal is inserted into the decompressed bitstream while detection is performed using the uncompressed video. This method allows detection if video has been manipulated or its format changed. We embed the watermark in the lowest frequency components of each frame in the un-coded video by using wavelet transform. The watermark can be extracted directly from the decoded video without access to the original video. Experimental results show that the proposed method gives the watermarked video of better quality and is robust against MPEG coding, down sampling and re-encoding to other type of video format such as MPEG4, H.264

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1115-1126
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• 2003

In this paper, we propose modeling method for video data that represents structural and semantic contents of video data efficiently. Also, a browsing method that helps users easily understand and play the contents of video data is presented. The proposed modeling scheme consists of three layers such as raw data layer, content layer and key frame layer The content layer represents logical hierarchy and semantic contents of video data. We implement two kinds of browsers for playing video data and providing video contents. The playing browser plays video data and Presents the information of currently playing shot. The content browser allows users to browse raw data, structural information and semantic contents of video data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3668-3684
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• 2021

Video action recognition is widely used in video surveillance, behavior detection, human-computer interaction, medically assisted diagnosis and motion analysis. However, video action recognition can be disturbed by many factors, such as background, illumination and so on. Two-stream convolutional neural network uses the video spatial and temporal models to train separately, and performs fusion at the output end. The multi segment Two-Stream convolutional neural network model trains temporal and spatial information from the video to extract their feature and fuse them, then determine the category of video action. Google Xception model and the transfer learning is adopted in this paper, and the Xception model which trained on ImageNet is used as the initial weight. It greatly overcomes the problem of model underfitting caused by insufficient video behavior dataset, and it can effectively reduce the influence of various factors in the video. This way also greatly improves the accuracy and reduces the training time. What's more, to make up for the shortage of dataset, the kinetics400 dataset was used for pre-training, which greatly improved the accuracy of the model. In this applied research, through continuous efforts, the expected goal is basically achieved, and according to the study and research, the design of the original dual-flow model is improved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.782-804
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• 2011

In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.39-44
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• 2009

In order to make the effect of the navigation system more direct, the paper proposes a thought of vehicle navigation system based on Video-GIS. A semantic framework has been defined whose core is focused on the integration and interaction of video and spatial information, which supports full content retrieval based on multimodal metadata extraction and fusion, and supports kinds of wireless access mode. Furthermore, requirements of prototype system are discussed. Then the design and implementation of framework are discussed. Next, describe the key ideas and technologies involved. Finally, we point out its future research trend.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3200-3219
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• 2013

This paper proposes an adaptive combined scalable video coding (CSVC) system for video transmission over MIMO-OFDM (Multiple-Input Multiple-Output-Orthogonal Frequency Division Multiplexing) broadband wireless communication systems. The scalable combination method of CSVC adaptively combines the medium grain scalable (MGS), the coarse grain scalable (CGS) and the scalable spatial modes with the limited feedback partially from channel state information (CSI) of MIMO-OFDM systems. The objective is to improve the average of peak signal-to-noise ratio (PSNR) and bit error rate (BER) of the received video stream by exploiting partial CSI of video sources and channel condition. Experimental results show that the delivered quality using the proposed adaptive CSVC over MIMO-OFDM system performs better than those proposed previously in the literature.