• Cartoon and Animation Studies
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• s.36
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• pp.349-374
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• 2014

The light is the language. Directors have to describe the scene component effectively his intention to configure the scene as an appropriately. After this act of the character, the layout of the props and scene lights will enter to the scene components. Those things help to audiences can understand narrative of work and emotion that producer want to send. Expressing their emotions especially using the lights by adjusting the colors and contrast makes audience to concentrate on work and understand naturally. This lighting technique clearly appears on early year theaters stage of England and Rembrandt's paintings. Properly dividing and controlling the lights dramatically increases the beauty of the work elements to express a variety of emotions such as worries and fear. Therefore, it can be evolve depending on director's intent of using lights on his work. Lights can increase involvement of human emotion through basic features that cognition of object, visualization of space-time and by artistic method in the product. This study will examine the role and how to use lighting to express the proper sentiment based on the narrative of the work. Making research named "Lighting Research of 3D animated film which applying light features to express emotion" previous study and have to combine emotional vocabulary and emotion-based theory for classifying the emotional language that can be applied on 3D animation. And choosing most emotional scene from 3D animation for analyze how they used lighting to expressing emotions. Directors trying to show up about the light role through light method that matched perfectly with an emotional language. Expecting this research work of directing 3D animations light for expressing emotional feelings will be continue successfully.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.311-317
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• 2017

A drama, generally composed of dozens of times, is one of the most popular broadcasting program genres, and it has the characteristics that the status and interrelationships of characters are changing as time goes on and important acts affecting the story occur sporadically. Therefore, when viewers missed some times in the middle of a drama, it is difficult to understand the drama without the changed information on the characters and notable actions. This paper proposes a data service which provides the updated information of the characters and important acts based on the drama scene. The data service has the characteristics that it provides the information on the characters shown in the current drama scene, and the information about the people mentioned in the dialogue in the scene. This paper includes a general introduction to the data services, the formal definition of the drama scene identification and character information, and an DVB-SI-based method for transmitting the information to the data service.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.423-430
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• 2023

This dissertation discusses the formulation of a nonlinear storytelling board that preserves the contextual perspective of characters. Storytelling encompasses the director's creative intention by leveraging the interaction of various elements to construct a logical narrative that explores cause and effect. Its primary objective is to enhance viewers' empathy. Consequently, there is a pressing need for comprehensive research on differentiating storytelling from storyboarding. Moreover, the integrated approach to storytelling and storyboarding holds scholarly value in understanding the process of narrative composition and visualization. Thus, a study proposes a method for constructing nonlinear storytelling boards considering the discrete camera perspective and contextual scene continuity, ultimately contributing to visual complexity and correlation comprehension. This approach enables a careful and simultaneous consideration of the correlations that deepen cognition, including the physical, emotional, and event rhythms mentioned in Karen Perlman's theory.

• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.289-292
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• 2008

본 논문에서는 사용자에게 보다 효율적이고 직관적인 비디오 브라우징 서비스를 제공하기 위하여 비디오 데이터의 종류와 특성에 제한받지 않고 강건하게 적용될 수 있는 장면전환 검출 알고리즘을 제안하고자 한다. 제한된 알고리즘은 명암 값의 급 변화나 객체의 빠른 움직임, 영상의 왜곡 등에 의한 장면전환 검출의 오류를 제거할 수 있으며, 특히 연속된 프레임사이의 강건한 차이 값 추출을 위한 개선된 식을 제안하고, 추출된 차이 값들로부터 변화패턴을 학습하고 특징을 추출함으로서 자동 임계치 결정에 활용하였다. 제안된 방법은 급진적인 장면변화가 많고 플래시라이트와 같은 조명의 변화가 많은 다양한 비디오 데이터를 가지고 실험되었으며, 실험결과 기존의 방법에 비교하여 효율적이고 신뢰할 수 있는 결과 값들을 보여주었다.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.549-561
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• 2007

Vision-based scene understanding is to infer and interpret the context of a scene based on the evidences by analyzing the images. A probabilistic approach using Bayesian networks is actively researched, which is favorable for modeling and inferencing cause-and-effects. However, it is difficult to gather meaningful evidences sufficiently and design the model by human because the real situations are dynamic and uncertain. In this paper, we propose a learning method of Bayesian network that reduces the computational complexity and enhances the accuracy by searching an efficient BN structure in spite of insufficient evidences and training data. This method represents the domain knowledge as ontology and builds an efficient hierarchical BN structure under constraint rules that come from the ontology. To evaluate the proposed method, we have collected 90 images in nine types of circumstances. The result of experiments indicates that the proposed method shows good performance in the uncertain environment in spite of few evidences and it takes less time to learn.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.11 no.5
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• pp.41-50
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• 1993

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.727-731
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• 2020

인공신경망의 예측 결과에 대한 원인을 분석하는 것은 모델을 신뢰하기 위해 필요한 작업이다. 이에 컴퓨터 비전 분야에서는 돌출맵 또는 히트맵의 형태로 모델이 어떤 내용을 근거로 예측했는지 시각화 하는 모델 해석 방법들이 제안되었다. 하지만 오디오 분야에서는 스펙트로그램 상의 시각적 해석이 직관적이지 않으며, 실제 어떤 소리를 근거로 판단했는지 이해하기 어렵다. 따라서 본 연구에서는 히트맵의 청취 분석 시스템을 제안하고, 이를 활용한 음향 장면 분류 모델의 히트맵 청취 분석 실험을 진행하여 인공신경망의 예측 결과에 대해 사람이 이해할 수 있는 설명을 제공할 수 있는지 확인한다.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.778-786
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• 2002

Scene boundary detection is important in the understanding of semantic structure from video data. However, it is more difficult than shot change detection because scene boundary detection needs to understand semantics in video data well. In this paper, we propose a new approach to scene segmentation using contextual information in video data. The contextual information is divided into two categories: local and global contextual information. The local contextual information refers to the foreground regions' information, background and shot activity. The global contextual information refers to the video shot's environment or its relationship with other video shots. Coherence, interaction and the tempo of video shots are computed as global contextual information. Using the proposed contextual information, we detect scene boundaries. Our proposed approach consists of three consecutive steps: linking, verification, and adjusting. We experimented the proposed approach using TV dramas and movies. The detection accuracy of correct scene boundaries is over than 80%.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.139-145
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• 2003

When a director produces motion frame with angle of camera, a director has intention of framework about each frame of animation. Charactors who appear in scene are element that have embodied intended motion of writer most faithfully and their motion acts important role to understand relevant work. Characters of frame are elements. In "Princess Mononoke", We study the characteristic of analyzing the characters'motion through structure of psychological conflict in animation.animation.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.75-82
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• 2002

Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper Propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with χ2 histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.