• Journal of KIISE:Computing Practices and Letters
• /
• v.9 no.1
• /
• pp.1-12
• /
• 2003

Recently, many researches into distributed processing on Internet, and multimedia data processing have been performed. Rapid and convenient multimedia services supplied with high quality and high speed are to be needed. In this paper, we design and implement clip-based video retrieval system on the Web enviroment in real-time. Our system consists of the content-based indexing system supporting convenient services for video content providers, and the Web-based retrieval system in order to make it easy and various information retrieval for users in the Web. Three important methods are used in the content-based indexing system, key frame extracting method by dividing video data, clip file creation method by clustering related information, and video database construction method by using clip unit. In Web-based retrieval system, retrieval method ny using a key word, two dimension browsing method of key frame, and real-time display method of the clip are used. In this paper, we design and implement the system that supports real-time display method of the clip are used. In this paper, we design and implement the system that supports real-time retrieval for video clips on Web environment and provides the multimedia service in stability. The proposed methods show a usefulness of video content providing, and provide an easy method for serching intented video content.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.6
• /
• pp.309-314
• /
• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38C no.7
• /
• pp.630-642
• /
• 2013

To transmit vital signal stream of mobile patients remotely, it requires mobility of patient and watcher, sensing function of patient's abnormal symptom and self-organizing service binding of related computing resources. In the existing relative researches, the vital signal stream is transmitted as a centralized approach which exposure the single point of failure itself and incur data traffic to central server although it is localized service. Self-organizing middleware platform based on heterogenous overlay network is a middleware platform which can transmit real-time data from sensor device(including vital signal measure devices) to Smartphone, TV, PC and external system through overlay network applied self-organizing mechanism. It can transmit and save vital signal stream from sensor device autonomically without arbitration of management server and several receiving devices can simultaneously receive and display through interaction of nodes in real-time.

• Journal of Korea Multimedia Society
• /
• v.14 no.7
• /
• pp.849-857
• /
• 2011

Gaming on demand(GOD) makes people enjoy games by encoding and transmitting game screen at a server side, and decoding the video at a client side. In this paper, we propose a fast game video encoder for multiple users over network with low-powered devices. In the proposed system, the computational complexity of game encoders is reduced by using scene descriptors, which consists of an object motion vector, global motion, and scene change. With additional information from game engines, the proposed encoder does not need to perform various complexity processes such as motion estimation and ratedistortion optimization. The motion estimation and rate-distortion optimization skipped by scene descriptors. We found that the proposed method improved 192 % in terms of FPS, compared with x264 software. With partial assembly code, we also improved coding speed by 86 % in terms of FPS. We found that the proposed fast encoder could encode over 60 FPS for real-time GOD applications.

• Proceedings of the Korea Contents Association Conference
• /
• 2007.11a
• /
• pp.140-145
• /
• 2007

The Lambda Networking is emerging to provide the high bandwidth stably for advanced applications such as a large file transfer in High Energy Physics and an Uncompressed HDTV streaming. The User Controlled LightPath(UCLP) is a software to facilitate the Lambda Networking. The UCLP is scalable as using Web Services to define and manage network resources. In this paper, we describe how we deployed the UCLP into KREONet2 and GLORIAD-KR. We also present that the original UCLP creates only a link-level APN due to a SONET technology. As employing a Virtual LAN (VLAN) of the layer2 technology in the UCLP, we can efficiently create a network-level APN.

• Journal of the Institute of Convergence Signal Processing
• /
• v.24 no.1
• /
• pp.42-50
• /
• 2023

The development of technology has achieved digital innovation throughout the media industry, including production techniques and editing technologies, and has brought diversity in the form of consumer viewing through the OTT service and streaming era. The convergence of big data and deep learning networks automatically generated text in format such as news articles, novels, and scripts, but there were insufficient studies that reflected the author's intention and generated story with contextually smooth. In this paper, we describe the flow of pictures in the storyboard with image caption generation techniques, and the automatic generation of story-tailored scenarios through language models. Image caption using CNN and Attention Mechanism, we generate sentences describing pictures on the storyboard, and input the generated sentences into the artificial intelligence natural language processing model KoGPT-2 in order to automatically generate scenarios that meet the planning intention. Through this paper, the author's intention and story customized scenarios are created in large quantities to alleviate the pain of content creation, and artificial intelligence participates in the overall process of digital content production to activate media intelligence.