• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1014-1028
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• 2012

Recently, N-screen service and secondary device have gotten an attention from public. Also, we can experience N-screen service through various digital devices. N-screen means multimedia technology which can seamlessly consume multimedia content. Secondary device means auxiliary multimedia device which can consume content related to main content through adjunct connection to main device. Not only be electronic manufactures interested in N-screen technology and services but also digital devices applied for N-screen have been released. But it has limitation that user can only consume content to be purchased from content company server not device of user. This paper proposes the system that composes effective and various N-screen multimedia service through MPEG-4 LASeR (Lightweight Application Scene Representation) PMSI (Presentation and Modification of Structured Information) as international standard technology which can provide scene description including many instruction for dynamic update of scene.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.98.3-98
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• 2002

Vision-based systems for finding road lanes have to operate robustly under a wide variety of environ-mental conditions including large amount of scene clutters. This paper presents a method for finding the lane boundaries by combining a local line extraction method and dynamic programming as a search tool. The line extractor obtains an initial position estimation of road lane boundaries from the noisy edge fragments. Dynamic programming then improves the initial approximation to an accurate configuration of lane boundaries. Input image frame is divided into a few sub-regions along the vertical direction. The local line extractor then performs to extract candidate lines of road lanes in the...

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.2
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• pp.73-79
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• 2015

Dynamic culling scheme is usually implemented to handle overhead caused by rendering the massive large-scale terrain data in flight simulator. However, existing culling scheme without considering altitude is not suitable for flight simulator due to additional computational overhead. To solve this problem, in this paper, we propose hybrid approach by applying two dynamic culling schemes depending on altitude. In addition, we remove unnessary computational overhead by creating different z-map resolution when aircraft changes its altitude. The proposed scheme is implemented with open graphic library and tested with real terrain data. Through the experimental results, we can recognize the improved rendering speed about 8 to 73 percents as compared to existing scheme.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.104-112
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• 2012

Recently, the HDR imaging technique that mimics human eye is incorporated with LCD/LED display devices to deal with mismatch between the real world scene and the displayed image. However, HDR image has a veiling glare limit as well as a scale of the local contrast problem. In order to overcome these problems, several color correction methods, CSR(center/surround Retinex), MSR (Multi-Scale Retinex), tone-mapping method, iCAM06 and so on, are proposed. However, these methods have a dominated color throughout the entire resulting image after performing color correction. Accordingly, this paper presents a new color correction method using dynamic cone response function. The proposed color correction method consists of tone-mapping and dynamic cone response. The tone-mapping is obtained by using a linear interpolation between chromatic and achromatic. Thereafter, the resulting image is processed through the dynamic cone response function, which estimates the dynamic responses of human visual system as well as deals with mismatch between the real scene image and the rendered image. The experiment results show that the proposed method yields better performance of color correction over the conventional methods.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.430-432
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• 2002

위성기술의 발달로 대규모의 고해상도 지형정보 생성이 가속화되고, 사실적 지형묘사 요구는 더욱 높아지고 있으므로 대규모 지형자료를 효율적으로 처리하여 실제감을 주는 고 충실도 렌더링 기법이 필수적이다. 본 연구에서는 지형 셀의 쿼드트리 구조를 기반으로 지형특성을 고려한 고속의 시계범위 컬링기법, 시각 거슬림 현상을 최소화하기 위한 연속적인 다단계 상세도 기법 및 기하모핑 기법, 일정한 폴리곤 수에 맞도륵 렌더링하는 프레임 균일화 기법 및 텍스쳐 관리기법 등의 효율적인 장면처리 기법을 제안한다.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.5
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• pp.277-285
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• 2016

Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3769-3789
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• 2018

Social pedestrian groups are the basic elements that constitute a crowd; therefore, detection of such groups is scientifically important for modeling social behavior, as well as practically useful for crowd video understanding. A social group refers to a cluster of members who tend to keep similar motion state for a sustained period of time. One of the main challenges of social group detection arises from the complex dynamic variations of crowd patterns. Therefore, most works model dynamic groups to analysis the crowd behavior, ignoring the existence of stationary groups in crowd scene. However, in this paper, we propose a novel unified framework for detecting social pedestrian groups in crowd videos, including dynamic and stationary pedestrian groups, based on spatiotemporal-oriented energy measurements. Dynamic pedestrian groups are hierarchically clustered based on energy flow similarities and trajectory motion correlations between the atomic groups extracted from principal spatiotemporal-oriented energies. Furthermore, the probability distribution of static spatiotemporal-oriented energies is modeled to detect stationary pedestrian groups. Extensive experiments on challenging datasets demonstrate that our method can achieve superior results for social pedestrian group detection and crowd video classification.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.9-18
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• 2013

In order to measure the parameters of consumers' preferred image quality, this research suggests image quality assessment factors; dynamic range, color, and contrast. They have both physical image quality factors and psychological characteristics from the previous researches. We found out the specific ranges of preferred image quality metrics. As a result, Digital Zone System meant for dynamic range generally shows 6~10 stop ranges in portrait, nightscape, and landscape. Total RGB mean values represent in portrait (67.2~215.2), nightscape (46~142), and landscape (52~185). Portrait total RGB averages have the widest range, landscape, and nightscape, respectively. Total scene contrast ranges show in portrait (196~589), nightscape (131~575), and landscape (104~767). Especially in portrait, skin tone RGB mean values are in ZONE V as the exposure standard, but practically image consumers' preferred skin tone level is in ZONE IV. Also, total scene versus main subject contrast ratio represents 1:1.2; therefore, we conclude that image consumers prefer the out-of-focus effect in portrait. Throughout this research, we can measure the preferred image quality metrics ranges. Also, we expect the practical and specific dynamic range, color, and contrast information of preferred image quality to positively influence product development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1846-1863
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• 2016

High dynamic range (HDR) images can present the perfect real scene and rich color information. A commonly encountered problem in practical applications is how to well visualize HDR images on standard display devices. In this paper, we propose a multi-scale decomposition method using guided filtering for HDR image tone mapping. In our algorithm, HDR images are directly decomposed into three layers：base layer, coarse scale detail layer and fine detail layer. We propose an effective function to compress the base layer and the coarse scale detail layer. An adaptive function is also proposed for detail adjustment. Experimental results show that the proposed algorithm effectively accomplishes dynamic range compression and maintains good global contrast as well as local contrast. It also presents more image details and keeps high color saturation.