• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.254-257
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• 2014

Recently, various applications using real-time face detection have been developed as face recognition technology and hardware grows. While network service is developing and video instruments costs lower, it is needed that smart surveillance camera and service using network camera based on IP and face detection technology. However, videos should be compressed for reducing network bandwidth and storage capacity in surveillance system. As it requires high-level improvement of system performance when all the compressed frames are processed in a face detection program, fast face detection method is needed. In this paper, not only a fast way of algorithm using Haar like features and adaboost learning and motion information but also an application on broadcast system is suggested.

• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.100-107
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• 2008

The aim of this paper is to design an intelligent character manipulation system suitable for the wireless broadband network environment named as Wibro and for the recent social networking service (SNS). The main feature of our proposed system is an automatic synthesis of a character utilizing the meta data which is attached to each component stored in a character database. It is the second advantageous feature that a user can make or modify his or her own character by modifying the component animation clip of its character. Once the character database is created, it can be represented and utilized in several ways by utilizing the meta data which is related to personal properties including emotion, life style, favorite things, and so on. The system can be evolved to a more powerful one by adopting the more user-related information and the more intelligent synthesis module.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.103-112
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• 2012

Recently, the infrastructure to be connected to the internet is much provided, there is more and more need to connect electric or electronic products to the internet to monitor or control them remotely. However, most of the existing products lack the network interface, so it was very inconvenient to be connected to the internet. Therefore, this article designs and realizes the internet outlet allowing real-time scheduling that can control the power remotely on the internet by using the hardware TCP/IP processor. The realized product consumes low production cost because it can be realized by using the hardware TCP/IP processor and the 8-bit small microprocessor. In addition, the product can be used widely in both wired and wireless environments with a variety of user interface, including the dedicated control program which provides the environment configuration functions; embedded web service that enables the webpage to be saved on the external flash memory; Android smartphone application; motion recognition control environment that uses the OpenCV computer vision library, etc.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.797-804
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• 2017

A social network is a typical social science environment with both network and iteration characteristics. This research presents a reaction analysis model of how each node responds to social networks when given input such as promotions or incentives. In addition, the setting value of a specific node is changed while examining the response of each node. And we try to understand the reactions of the nodes involved. The reaction analysis model is constructed by applying various techniques such as unidirectional, fuzzy set, weighting, and cyclic feedback, so it can accommodate the complicated environment of practice. Finally, the implementation model is implemented using Vensim rather than NetLogo because it requires repetitive input, change of setting value in real time, and analysis of association between nodes.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.365-374
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• 2011

Recently, malicious video classification and filtering techniques are of practical interest as ones can easily access to malicious multimedia contents through the Internet, IPTV, online social network, and etc. Considerable research efforts have been made to developing malicious video classification and filtering systems. However, the malicious video classification and filtering is not still being from mature in terms of reliable classification/filtering performance. In particular, the most of conventional approaches have been limited to using only the spatial features (such as a ratio of skin regions and bag of visual words) for the purpose of malicious image classification. Hence, previous approaches have been restricted to achieving acceptable classification and filtering performance. In order to overcome the aforementioned limitation, we propose new malicious video classification framework that takes advantage of using both the spatial and temporal features that are readily extracted from a sequence of video frames. In particular, we develop the effective temporal features based on the motion periodicity feature and temporal correlation. In addition, to exploit the best data fusion approach aiming to combine the spatial and temporal features, the representative data fusion approaches are applied to the proposed framework. To demonstrate the effectiveness of our method, we collect 200 sexual intercourse videos and 200 non-sexual intercourse videos. Experimental results show that the proposed method increases 3.75% (from 92.25% to 96%) for classification of sexual intercourse video in terms of accuracy. Further, based on our experimental results, feature-level fusion approach (for fusing spatial and temporal features) is found to achieve the best classification accuracy.

• Geophysics and Geophysical Exploration
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• v.14 no.4
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• pp.298-304
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• 2011

We conducted magnetic survey using IBRV (Ice Breaker Research Vessel) ARAON of KORDI (Korea Ocean Research and Development Institute), ROV (Remotely Operated Vehicle) of Oceaneering Co. and three components vector magnetometer, at Apr., 2011 in the western slope of the caldera of TA25 seamount, the Lau Basin, the southwestern Pacific. The depth ranges of the survey area are from about 900 m to 1200 m, below sea level. For the deep sea magnetic survey, we made the nation's first small deep sea three components magnetometer of Korea. The magnetometer sensor and the data logger was attached with the upper part and lower part of ROV, respectively. ROV followed the planning tracks at 25 ~ 30 m above seafloor using the altimeter and USBL (Ultra Short Base Line) of ROV. The three components magnetometer measured the X (North), Y (East) and Z (Vertical) vector components of the magnetic field of the survey area. A motion sensor provided us the data of pitch, roll, yaw of ROV for the motion correction of the magnetic data. The data of the magnetometer sensor and the motion sensor were recorded on a notebook through the optical cable of ROV and the network of ARON. The precision positions of magnetic data were merged by the post-processing of USBL data of ROV. The obtained three components magnetic data are entirely utilized by finding possible hydrothermal vents of the survey area.

• The Journal of the Korea Contents Association
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• v.12 no.1
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• pp.91-102
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• 2012

Generally today's culture and the arts industry has been focusing more on economic value than the arts. Therefore this paper will elucidate the meaning of the culture and the arts can be a break though which can only include commercial and economic values but transcend its values ultimately. First of all, this paper will suggest an advanced 3D stereoscopic images by analysis of examples and environments of realistic media arts. Looking into the changes of related technologies and market environments, the motion-recognition technology, as seem in SF film "Minority report", has become a feasible technology. In the past, 3D stereoscopic images were shown in the theme park theatre and exhibition halls for group viewing. but recent 3D TV and display devices have changed those environments to personal. Since domestic researches of realistic media art has been little, this paper will analyze them respecting to three broad classifications. The results are : Firstly, in CAVE method, more impact capabilities of spectators are expected that they can manipulate interactive interfaces freely and the physical movements of spectators can operate interactively. Secondly, inter-network communications and expansion of viewers' perceptions are predicted by way of HMD method, sensor suites and communication equipments. Thirdly, combinations of HMD and motion tracking utilization is foreseen. With the convergent usages of these three features, we can prospect the possibilities of interactive 4D that spectators wearing 3D stereoscopic display devices can experience and make their own 3D stereoscopic images actively at the point of their views.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.575-584
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• 2008

According to the network condition, the communication network overload could be occurred when media transmitting. Many researches are being carried out to lessen the network overload, such as the filtering, load distributing, frame dropping and many other methods. Among these methods, one of effective method is frame dropping that reduces specified video frames for bandwidth diminution. B frames are dropped and then I, P frames are dropped according to dependency among the frames in frame dropping. This paper proposes a scheme for protecting copyrights by encryption, when we apply frame dropping to reduce bandwidth of media following MPEG-4 file format. We designed two kinds of frame dropping: first one stores and then sends the dropped files and the other drops frames in real-time when transmitting. We designed three kinds of encryption methods in which DES algorithm is used to encrypt MPEG-4 data: macro block encryption in I-VOP, macro block and motion vector encryption in P-VOP, and macro block and motion vector encryption in I, P-VOP. Based on these three methods, we implemented a digital right management solution for MPEG-4 data streaming. We compared the results of dropping, encryption, decryption and quality of video sequences to select an optimal method, and there is no noticeable difference between the video sequences recovered after frame dropping and the ones recovered without frame dropping. The best performance in encryption and decryption of frames was obtained when we apply the macro block and motion vector encryption in I, P-VOP.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.69-78
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• 2022

As the use of Internet of Things (IoT) devices has expanded, digital forensics coverage of the National Police Agency has expanded to smart home areas. Accordingly, most of the existing studies conducted to acquire smart home platform data were mainly conducted to analyze local data of mobile devices and analyze network perspectives. However, meaningful data for evidence analysis is mainly stored on cloud storage on smart home platforms. Therefore, in this paper, we study how to acquire stored in the cloud in a Hey Home Air environment by extracting accessToken of user accounts through a cookie database of browsers such as Microsoft Edge, Google Chrome, Mozilia Firefox, and Opera, which are recorded on a PC when users use the Hey Home app-based "Hey Home Square" service. In this paper, the it was configured with smart temperature and humidity sensors, smart door sensors, and smart motion sensors, and artifacts such as temperature and humidity data by date and place, device list used, and motion detection records were collected. Information such as temperature and humidity at the time of the incident can be seen from the results of the artifact analysis and can be used in the forensic investigation process. In addition, the cloud data acquisition method using OpenAPI proposed in this paper excludes the possibility of modulation during the data collection process and uses the API method, so it follows the principle of integrity and reproducibility, which are the principles of digital forensics.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.