• Title/Summary/Keyword: Emotion Visualization

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Emotion-based music visualization using LED lighting control system (LED조명 시스템을 이용한 음악 감성 시각화에 대한 연구)

  • Nguyen, Van Loi;Kim, Donglim;Lim, Younghwan
    • Journal of Korea Game Society
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    • v.17 no.3
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    • pp.45-52
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    • 2017
  • This paper proposes a new strategy of emotion-based music visualization. Emotional LED lighting control system is suggested to help audiences enhance the musical experience. In the system, emotion in music is recognized by a proposed algorithm using a dimensional approach. The algorithm used a method of music emotion variation detection to overcome some weaknesses of Thayer's model in detecting emotion in a one-second music segment. In addition, IRI color model is combined with Thayer's model to determine LED light colors corresponding to 36 different music emotions. They are represented on LED lighting control system through colors and animations. The accuracy of music emotion visualization achieved to over 60%.

A Study on Non-Verbal Expressions for the Realization of Narrative Visualization -Focusing on a 3D Cat Character, "Puss" (내러티브 시각화 구현을 위한 비언어적 표현 연구-3D 고양이 캐릭터 "Puss"를 중심으로)

  • Lee, Young-Suk;Kim, Sang-Nam
    • Journal of Korea Multimedia Society
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    • v.19 no.3
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    • pp.659-672
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    • 2016
  • In animated films, characters materialize narratives through acting. The narrative is an element to materialize accurate delivery of lines and emotions. The non-verbal actions should express lots of emotions and lines in scenes, and also they can be used as a way of empathy. This study analyzed the visualization factors of narrative focusing on a cat character frequently shown in animated films. For this, the visualization factors of non-verbal actions expressed in characters' personal space and dynamic space were extracted. Based on this, it aims to suggest the emotion expressing method of characters to realize effective narrative visualization. In the future, it aims to be used as reference data in case when producing non-verbal communication for 3D characters.

Visualization Study of Character Type by Emotion Word Extraction (감정어 추출을 통한 등장인물 성향 가시화 연구)

  • Baek, Yeong Tae;Park, Seung-Bo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2013.07a
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    • pp.31-32
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    • 2013
  • 본 논문에서는 영화의 등장인물의 성향을 파악하기 위해 시나리오의 대사로부터 감정어를 추출하고, 등장인물의 감정어들을 긍정, 부정, 중립의 3개로 단순화하여 등장인물의 성향을 가시화 시켜주는 방법을 제안한다. 대사로부터 감정어를 추출하기 위해 WordNet 기반의 감정어 추출 방법을 제안한다. WordNet은 단어 간에 상위어와 하위어, 유사어 등의 관계로 연결된 네트워크 구조의 사전이다. 이 네트워크 구조에서 최상위의 감정 항목과의 거리를 계산하여 단어별 감정량을 계산하여 대사를 30 차원의 감정 벡터로 표현한다. 등장인물별로 추출된 감정 벡터를 긍정, 부정, 중립의 3개의 차원으로 단순화 하여 등장인물의 성향을 표현한다.

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Visualization using Emotion Information in Movie Script (영화 스크립트 내 감정 정보를 이용한 시각화)

  • Kim, Jinsu
    • Journal of the Korea Convergence Society
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    • v.9 no.11
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    • pp.69-74
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    • 2018
  • Through the convergence of Internet technology and various information technologies, it is possible to collect and process vast amount of information and to exchange various knowledge according to user's personal preference. Especially, there is a tendency to prefer intimate contents connected with the user's preference through the flow of emotional changes contained in the movie media. Based on the information presented in the script, the user seeks to visualize the flow of the entire emotion, the flow of emotions in a specific scene, or a specific scene in order to understand it more quickly. In this paper, after obtaining the raw data from the movie web page, it transforms it into a standardized scenario format after refining process. After converting the refined data into an XML document to easily obtain various information, various sentences are predicted by inputting each paragraph into the emotion prediction system. We propose a system that can easily understand the change of the emotional state between the characters in the whole or a specific part of the various emotions required by the user by mixing the predicted emotions flow and the amount of information included in the script.

Facial Data Visualization for Improved Deep Learning Based Emotion Recognition

  • Lee, Seung Ho
    • Journal of Information Science Theory and Practice
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    • v.7 no.2
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    • pp.32-39
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    • 2019
  • A convolutional neural network (CNN) has been widely used in facial expression recognition (FER) because it can automatically learn discriminative appearance features from an expression image. To make full use of its discriminating capability, this paper suggests a simple but effective method for CNN based FER. Specifically, instead of an original expression image that contains facial appearance only, the expression image with facial geometry visualization is used as input to CNN. In this way, geometric and appearance features could be simultaneously learned, making CNN more discriminative for FER. A simple CNN extension is also presented in this paper, aiming to utilize geometric expression change derived from an expression image sequence. Experimental results on two public datasets (CK+ and MMI) show that CNN using facial geometry visualization clearly outperforms the conventional CNN using facial appearance only.

Grouping and Visualization of Preferred Sensations among College students (선호하는 감성어휘 분석을 통한 남녀대학생의 감성 유형화)

  • 한경미;나영주;조길수
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2001.11a
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    • pp.15-18
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    • 2001
  • 98가지 감성 형용사를 수집하여 176명의 남녀대학생을 대상으로 SD법에 의해 선호도를 조사한 결과, 선호감성어휘는 '로맨틱, 센수얼, 캐주얼, 클래식, 캐릭터, 프린스, 심플, 복고풍, 모던, 수공예, 테크노' 등으로 요약되었는데 이를 바탕으로 군집분석을 시행하여 선호 감성을 유형화시켰다. 남녀대학생이 선호감성은 크게 10가지의 유형으로 나타났는데, 대부분의 대학생들이 '캐주얼파였으나(32.4%), 이는 구체적으로 '비장식개성캐주얼파, 역동쿨개성캐주얼파'였으며, 다음으로는 '단순내추럴파'가 17.3%였다. 이후 '클래식파(9.2%-수공예로맨틱클래식파, 획일적클래식파', '비표현파(8.7%)', '호화개성복고파(6.4%)', '민족감성선호파(4.6%)' 등이 있었다. 대학생을 집단들은 크게 두 개의 선호 감성축(정적-동적, 경량-중량)을 중심으로 가시적으로 그룹화 될 수 있었다.

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