• Journal of Korea Society of Industrial Information Systems
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• v.9 no.3
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• pp.71-79
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• 2004

Owing to the rapid increase of the number of automobiles, the traffic is being heavily crippled as time goes by. To provide drivers with better safety and convenience, a variety of CNSs(Car Navigation System) are being installed more and more specially for the vehicles which are produced in recent days. As the CNS has gained the public popularity, it has been playing a role as a component of the multimedia system in a vehicle in addition to providing the capability of route guidance service. It is, therefore, now recognized as an important unit of the vehicle interior system. As the situation has been changed as formerly described, it is necessary that not only the functions but also the usability and exterior features are to be designed to suit customers' tastes. This paper is an attempt to find out what the major sensibility factors which customers want as far as a CNS is concerned are. Because these factors can differ from a vehicle type to another that customers prefer, the analysis is based on the vehicle preference. It is proved that MDS(Multi Dimensional Scaling) is an effective method to analyze the sensibility factors for the different types of vehicles. The result shows that for the people who prefer the sedan-type vehicles, luxuriousness, harmoniousness, and texture are major factors. For people who like sports car, faminism, salience, and dynamics are major factors. For people who prefer SUV's(Sports Utility Vehicle) or MPV's(Multi Purpose Vehicle), solidity, dynamics, and convenience are important.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.383-394
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• 2018

In this paper, we investigate image and video compression techniques based on deep learning which are actively studied recently. The deep learning based image compression technique inputs an image to be compressed in the deep neural network and extracts the latent vector recurrently or all at once and encodes it. In order to increase the image compression efficiency, the neural network is learned so that the encoded latent vector can be expressed with fewer bits while the quality of the reconstructed image is enhanced. These techniques can produce images of superior quality, especially at low bit rates compared to conventional image compression techniques. On the other hand, deep learning based video compression technology takes an approach to improve performance of the coding tools employed for existing video codecs rather than directly input and process the video to be compressed. The deep neural network technologies introduced in this paper replace the in-loop filter of the latest video codec or are used as an additional post-processing filter to improve the compression efficiency by improving the quality of the reconstructed image. Likewise, deep neural network techniques applied to intra prediction and encoding are used together with the existing intra prediction tool to improve the compression efficiency by increasing the prediction accuracy or adding a new intra coding process.

• Cartoon and Animation Studies
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• s.27
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• pp.177-198
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• 2012

Development of digital media and interest in education bring big progress at digital device of education globally. UK which is advanced country of education is using digital education devices such as digital chalkboards, digital desks etc. and Japan plan digital text book's through the state. At 2011, Korea which is advanced country of internet adopted digital text book 2007 with mathematics, through science and English digital text book through the state. Korea's digital textbook is in a transition period, that needs case-study of advanced country of education for setting design guide and educational effect to Digital text book plan. All researches are based on LG europe design center at London, UK and target countries are UK and Sweden which is advanced country of education and a welfare state. Analysis by using FGI, KJ, survey of questionnaire, heuristic method, concentration observation. Through analytical researches prefer using digital text book with paper text book to using solo that can offer each advantage to user and teacher. Especially Interactive GUI design of digital text book to easy to access for teacher whom not friendly with digital device. When plan Digital text book content and design needs methodical design guide for target who students and teachers an in-depth study of the appraisal and method. The results of the research are introduce the design plan as a basic research and giving useful design plan to make digital text book and digital educational media in industrial aspect.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1045-1055
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• 2007

Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.

• Journal of KIISE:Software and Applications
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• v.35 no.4
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• pp.207-218
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• 2008

With the growth of the Internet, multimedia streaming becomes an important means to deliver video contents over the Internet and the amount of the streaming multimedia contents is also getting increased. However, it becomes difficult to guarantee the quality of service in real-time over the IP network environment with instantaneously varying bandwidth. In this paper, we propose an optimal adaptation framework for streaming contents over the Internet in the sense that the perceptual quality of the multi-angie content with multiple visual objects is maximized given the constraints such as available bandwidth and transcoding cost. In the multi-angle video service framework, the user can select his/her preferred alternate views among the given multiple video streams captured at different view angles for a same event. This enhanced experience often entails streaming problems in real-time over the network, such as instantaneous bandwidth changes in the Internet. In order to cope with this problem, we assume that multi-angle video contents are encoded at different bitrates and the appropriate video streams are then selected or transcoded for delivery to meet such bandwidth constraints. For the user selective consumption of the various bitstreams in the multi-angle video service, the bitstream in each angle can be encoded in various bitrate, and the user can select a sub-bitrstream in the given bitrstreams or transcode the corresponding content in order to deliver the optimally adapted video contents to the instantaneously changing network condition. Therefore, we define the transcoding cost which means the time taken for transcoding the video stream and formulate a unified optimization framework which maximizes the perceptual quality of the multiple video objects in the given constraints such as the transcoding cost and the network bandwidth. Finally, we present plenty of the experimental results to show the effectiveness of the proposed method.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.144-153
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• 2009

Recently, as the necessity of a light-weighted video encoding technique has been rising for applications such as UCC(User Created Contents) or Multiview Video, Distributed Video Coding(DVC) where a decoder, not an encoder, performs the motion estimation/compensation taking most of computational complexity has been vigorously investigated. Wyner-Ziv coding reconstructs an image by eliminating the noise on side information which is decoder-side prediction of original image using channel code. Generally the side information of Wyner-Ziv coding is generated by using frame interpolation between key frames. The channel code such as Turbo code or LDPC code which shows a performance close to the Shannon's limit is employed. The noise model of Wyner-Ziv coding for channel decoding is called Virtual Channel Noise and is generally modeled by Laplacian or Gaussian distribution. In this paper, we propose a Wyner-Ziv coding method based on the frequency-adaptive channel noise modeling in transform domain. The experimental results with various sequences prove that the proposed method makes the channel noise model more accurate compared to the conventional scheme, resulting in improvement of the rate-distortion performance by up to 0.52dB.

• Cartoon and Animation Studies
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• s.17
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• pp.53-67
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• 2009

According to the changes of current regulation of media, the broadcasting environment has been loosened by market power, and came into competitive era for broadcasting industry with new technology of combined broadcasting and communication. To resolve these issues, the broadcasting provides are trying process of new channel brand identity to introduce their channels. The purpose of the research is to analyze Spot animation that has fast access to viewers among channel brand identity factors, review expandability and usage of Spot animation character to plan, manage character that can improve awareness and loyalty. Therefore it will study creation background and production, activities of each character representing KBS and MBC, compare the structure, color, material, expression of Spot animation character and summarize properties. To conclusion, three characters of KBS and MBC failed to apply structured and professional plan and management, only expressed image that each channel pursue on Station ID Spot animation and had issues of not deeply sighting expandability and usefulness as a character. The important factor to improve channel brand value of broadcasting provider is to have differentiated identity, and the core of it is to make image-responsible Station ID to be effective. Therefore, Spot animation and character of Station ID is a very important factor so there must be professional research and structural management from the early planning and production for character that represents the providers.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.471-482
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• 2006

In this paper, we propose a new scheme to generate multi-view images utilizing depth map decomposition and adaptive edge smoothing. After carrying out smooth filtering based on an adaptive window size to regions of edges in the depth map, we decompose the smoothed depth map into four types of images: regular mesh, object boundary, feature point, and number-of-layer images. Then, we generate 3-D scenes from the decomposed images using a 3-D mesh triangulation technique. Finally, we extract multi-view images from the reconstructed 3-D scenes by changing the position of a virtual camera in the 3-D space. Experimental results show that our scheme generates multi-view images successfully by minimizing a rubber-sheet problem using edge smoothing, and renders consecutive 3-D scenes in real time through information decomposition of depth maps. In addition, the proposed scheme can be used for 3-D applications that need the depth information, such as depth keying, since we can preserve the depth data unlike the previous unsymmetric filtering method.

• Journal of Broadcast Engineering
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• v.14 no.6
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• pp.733-741
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• 2009

The design rule of digital communication systems is the reliable data transmission with high spectral efficiency and minimum allowable power. This paper suggests the method that saves the average power by implementing a multi-dimensional constellation in case of multi-carrier communication system. By using multi-dimensional constellations we can relocate constellation points in the form of a sphere. If we simply convert the two-dimensional QAM modulation into multi-dimensional QAM, constellation points of 2 N dimensional cube form are made up. Relocating outermost constellation points of 2 N dimensional cube form into low energy constellation points, the constellation of the 2 N-dimensional sphere form is made up which decreases power consumption. In this paper, the multi-dimensional constellations of 2 N-dimensional sphere form are designed from 16-QAM to 2,048-QAM, and power reductions are obtained by comparing constellations of 2-dimensional QAMs and multi-dimensional constellations of 2 N-dimensional sphere form. The result shows that the average power consumption of higher dimensional constellations increases, because the more a dimension elevates, the more the relocatable constellation points increase. But, the increment of the average power savings decreases as the a dimension elevates. The transmission of the data by using multi-dimensional constellations of the sphere form is effective to save the average power consumption with little hardware complexity.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.313-321
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• 2014

In current society, the digital era that makes enormous amount of data, and the diversified city, the smart space, which has characteristics of creating, collecting and representing data, is appeared. After 2012, in the social media environment called hyper-connected society with wide-spread smart phone, people started to get interested in public data and big data by generalized mobile device and SNS. At first, development of forming platform of data was focused, but now, many different idea from diverse area have been suggested about data analysis and usage to visualize the space intellectualization service. To focus on the visualization process to increase the usage of this public data for ordinary people more than specialized people, this research grasps the present condition of open data and public data service from the current public data portal and considers the applicability of them. As the result of research, the analysis and application of data to ordinary people decrease the use of paper documents, and this research will help to develop the application which is fast and accurate about individual behavior and demand to utilize public data service in intellectual space.