• The KIPS Transactions:PartA
• /
• v.9A no.2
• /
• pp.207-216
• /
• 2002

This paper present a design and implementation of a distributed audio, Video stream service framework based on CORBA for efficient processing and control of audio/video stream. We design software components which support processing, control and transmission of audio/video streams as distributed objects. For optimization of stream transmission performance, we separate the transmission path of control data and media data. Distributed objects are defined by IDL and implemented using JAVA. And device dependent facilities like media capturing, playing and communication channels are implemented using JMF (Java Media Framework) components. We show a connection establishment and control procedure of streams communication. And for evaluation, we implement a test system and experiment a system performance. Our experiments show that test system has somewhat longer connection latency time compared to TCP connection establishment, but has optimized media transmission time compared to CORBA IIOP. Also test system show acceptable service quality of media transmission.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.5
• /
• pp.37-45
• /
• 2022

As of 2020, about 500 hours of videos are uploaded to YouTube, a representative online video platform, per minute. As the number of users acquiring information through various uploaded videos is increasing, online video platforms are making efforts to provide better recommendation services. The currently used recommendation service recommends videos to users based on the user's viewing history, which is not a good way to recommend videos that deal with specific purposes and interests, such as educational videos. The recent recommendation system utilizes not only the user's viewing history but also the content features of the item. In this paper, we extract the content features of educational video for educational video recommendation based on YouTube, design a recommendation system using it, and implement it as a web application. By examining the satisfaction of users, recommendataion performance and convenience performance are shown as 85.36% and 87.80%.

• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.15-30
• /
• 2023

Recently, various services using artificial intelligence(AI) are emerging in the media field as well However, most of the video editing, which involves finding an editing point and attaching the video, is carried out in a passive manner, requiring a lot of time and human resources. Therefore, this study proposes a methodology that can detect the edit points of video according to whether person in video are spoken by using Video Swin Transformer. First, facial keypoints are detected through face alignment. To this end, the proposed structure first detects facial keypoints through face alignment. Through this process, the temporal and spatial changes of the face are reflected from the input video data. And, through the Video Swin Transformer-based model proposed in this study, the behavior of the person in the video is classified. Specifically, after combining the feature map generated through Video Swin Transformer from video data and the facial keypoints detected through Face Alignment, utterance is classified through convolution layers. In conclusion, the performance of the image editing point detection model using facial keypoints proposed in this paper improved from 87.46% to 89.17% compared to the model without facial keypoints.

• Journal of Broadcast Engineering
• /
• v.25 no.3
• /
• pp.374-385
• /
• 2020

In this paper, we propose a preprocessing technique to solve the problems of action recognition with Equirectangular Projection (ERP) video. The preprocessing technique proposed in this paper assumes the person object as the subject of action, that is, the Object of Interest (OOI), and the surrounding area of the OOI as the ROI. The preprocessing technique consists of three modules. I) Recognize person object in the image with object recognition model. II) Create a saliency map from the input image. III) Select subject of action using recognized person object and saliency map. The subject boundary box of the selected action is input to the action recognition model in order to improve the action recognition performance. When comparing the performance of the proposed preprocessing method to the action recognition model and the performance of the original ERP image input method, the performance is improved up to 99.6%, and the action is obtained when only the OOI is detected. It can also see the effects of related video summaries.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.11a
• /
• pp.826-834
• /
• 2002

Asynchronous third generation mobile communication system is able to service Packet Switching through adding GPRS Network to the second generation system GSM. Therefore, it is necessary to study packet traffic service of GGSN node which is due to perform gateway role that GPRS Network is enable to inter-connect with Internet in order to optimize the capability and performance of GGSN. In this paper, the Internet packet traffic model that it is arrived to GGSN node from the Internet is studied and In order to process the Inter traffic efficiently, performance analysis model in GGSN is proposed to optimize packet processing capability of each processor. In order to guarantee QoS requirement of the real time traffic Speech and Video, several scheduling algorithm is applied to performance model and each mechanism is compared with several performance parameters.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.2A
• /
• pp.139-147
• /
• 2008

DVB-S2 (Digital Video Broadcasting-Satellite, Version 2) system transmits frames which adapt their structures based on the channel conditions, thus requiring simultaneous detection of the start of the Same (SoF) and the frame structure at the initial acquisition stage of the receiver. Also, a very low value of the minimum operating signal-to-noise ratio (SNR) for the acquisition necessitates a method utilizing multiple received frames to meet the required performance. In this paper, performance of joint time synchronization and frame structure detection methods using multiple DVB-S2 frames is evaluated by deriving the detection error probability. In particular, we evaluate the performance and complexity variations when the soft- and hard-decision values of the signal correlation output are used, present the synchronization parameters to optimize the performance, and verify the analysis results via computer simulations.

• Journal of Broadcast Engineering
• /
• v.2 no.2
• /
• pp.86-93
• /
• 1997

Fast growth of multimedia applications requires new functions for video data processing. such as obj;cted-based video representation and manipulation. which are not supported by 11PEG-l and 11PEG-2. To support these requirements. 11PEG-4 video coding allows users to manipulate every video object easily by decomposing a scene into several video objects and coding each of them independently. However. the large amount of computations and flexible structure of 11PEG-4 video CODEC make it difficult to be implemented by either the general purpose DSP or a dedicated VLSI. In this paper, we propose a hardware architecture using a hybrid of a high performance programmable DSP and an application specific IC to implement a flexible 11PEG-4 video codec requiring the large amount of computations. The application specific IC has the functions of motion estimation and compensation.

• The Journal of the Korea Contents Association
• /
• v.17 no.3
• /
• pp.329-336
• /
• 2017

In video compression, Motion Estimation(ME) limits the performance of image quality and generated bit rates. However, it requires much complexity in the encoder part. Multi-view video uses many cameras at different positions. Multi-view video coding needs huge computational complexity in proportion to the number of the cameras. To reduce computational complexity and maintain the image quality, an effective motion estimation method is proposed in this paper. The proposed method exploiting the characteristics of motion vector distribution and the motion of video. The proposed is a kind of a hierarchical search strategy. This strategy consists of multi-grid rhombus pattern, diagonal pattern, rectangle pattern, and refinement pattern. Experiment results show that the complexity reduction of the proposed method over TZ search method and PBS (Pel Block Search) on JMVC (Joint Multiview Video Coding) can be up to 40~75% and 98% respectively while maintaining similar video image quality and generated bit rates.

• Journal of KIISE
• /
• v.43 no.11
• /
• pp.1281-1297
• /
• 2016

In recent years, personal videos have seen a tremendous growth due to the substantial increase in the use of smart devices and networking services in which users create and share video content easily without many restrictions. However, taking both into account would significantly improve event detection performance because videos generally have multiple modalities and the frame data in video varies at different time points. This paper proposes an event detection method. In this method, high-level features are first extracted from multiple modalities in the videos, and the features are rearranged according to time sequence. Then the association of the modalities is learned by means of DNN to produce a personal video event detector. In our proposed method, audio and image data are first synchronized and then extracted. Then, the result is input into GoogLeNet as well as Multi-Layer Perceptron (MLP) to extract high-level features. The results are then re-arranged in time sequence, and every video is processed to extract one feature each for training by means of DNN.

• Journal of KIISE:Software and Applications
• /
• v.30 no.7_8
• /
• pp.610-617
• /
• 2003

Similarity matching in video database is of growing importance in many new applications such as video clustering and digital video libraries. In order to provide efficient access to relevant data in large databases, there have been many research efforts in video indexing with diverse spatial and temporal features. however, most of the previous works relied on sequential matching methods or memory-based inverted file techniques, thus making them unsuitable for a large volume of video databases. In order to resolve this problem, this paper proposes an effective and scalable indexing technique using a trie, originally proposed for string matching, as an index structure. For building an index, we convert each frame into a symbol sequence using a window order heuristic and build a disk-resident trie from a set of symbol sequences. For query processing, we perform a depth-first search on the trie and execute a temporal segmentation. To verify the superiority of our approach, we perform several experiments with real and synthetic data sets. The results reveal that our approach consistently outperforms the sequential scan method, and the performance gain is maintained even with a large volume of video databases.