• Title/Summary/Keyword: 물고기 움직임

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Propelling and Turning Motions of Fish for Virtual Aquarium (가상 수족관 물고기의 추진과 회전 유영 생성 방법)

  • Han, yoon-seok;Yoon, jae-hong;Kim, eun-seok
    • Proceedings of the Korea Contents Association Conference
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    • 2008.05a
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    • pp.33-37
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    • 2008
  • The interaction between artificial fish and aquatic surroundings and the fish's realistic locomotion are very important elements to construct virtual aquariums. In general, the artificial fish in virtual aquariums used to be created by 3D modeling tools, and was repeatedly showing the simple and constant form of swimming. This paper will analyze the sorts of biological forms of fish-swimming and the propelling and turning characteristics. Then, we propose a method of the basic swimming and turning of artificial fish to generate various and natural-looking locomotion. It is possible to make a explorable virtual aquarium more immersive by using interactive interfaces together.

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An Effective Feature Extraction for Polluted Fish′s Motion Analysis (오염 물고기 움직임 분석을 위한 효율적인 특징 추출)

  • 강민경;김도현;차의영;전태수;강진숙
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.04b
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    • pp.649-651
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    • 2002
  • 본 논문에서는 오염된 물고기의 특성을 자동으로 분석하기 위한 진보적 행동 분석 시스템을 제안한다. 이 행동 분석 시스템은 수질 생명체들을 오염으로부터 보호할 수 있도록 하기 위한 경보 시스템으로서, 물고기의 행동 특성을 Kohonen Neural Network를 사용하여 자동으로 군집화하고 분석할 수 있도록 하였다. 이때, Neural Network의 입력으로 사용하기 위한 특징 벡터는 물고기의 좌표 위치만을 사용하지 않고 위치 좌표를 바탕으로 속도, 가속도, 각속도, 각 가속도를 구하여 이를 사용함으로써 보다 효율적인 특징 추출이 이루어질 수 있도록 하였다. 오염 생명체와 비오염 생명체의 특징을 각각 추출하여 실험해 본 결과, 오염물질에 노출된 물고기의 밤(야간) 데이터에서 다른 군집과는 다른 뚜렷한 이상 행동 특성이 나타나는 것을 알 수 있었다.

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Polluted Fish`s Motion Analysis Using Self-Organizing Feature Maps (자기조직화 형상지도를 이용한 오염 물고기 움직임 분석)

  • 강민경;김도현;차의영;곽인실
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.316-318
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    • 2001
  • 본 논문에서는 자기조직화 형상지도(Self-organizing Feature Maps)를 사용하여 움직이는 물체에 대해 움직임의 특성을 자동으로 분석하였다. Kohonen Network는 자기조직을 형성하는 unsupervised learning 알고리즘으로서, 이 논문에서는 생태계에서의 데이터를 Patternizing하고, Clustering 하는데 사용한다. 본 논문에서 Kohonen 신경망의 학습에 사용한 데이터는 CCD 카메라로 물고기의 움직임을 추적한 좌표 데이터이며, diazinon 0.1 ppm을 처리한 물고기 점 데이터와 처리하지 않은 점 데이터를 각각 낮.밤 약 10시간동안 수집하여, \circled1처리전 낮 데이터 \circled2처리전 밤 데이터 \circled3처리전 낮 데이터 \circled4처리후 밤 데이터 각각 4개의 group으로 분류한 후, Kohonen Network을 사용하여 물고기의 행동 차이를 분석하였다.

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Research on Fish Animation Based on Advanced Skeleton plug-in (3D 물고기 애니메이션 효율성 향상을 위한 Advanced Skeleton plug-in 연구)

  • Li, Xiao;Lee, Byung-Chun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.361-363
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    • 2021
  • Digital character rigging is an important technology to improve animation vividness, and there are many kinds of complex ways of rigging system. To move naturally, the fish are tested for movement. Because 2,4 family role information although some, but the study of fish (0 family) action information is not much. As the diversity and complexity of fish production increases, inefficient time and capital are required. How to build a fish-like skeleton system depends on how to build an efficient and agile rigging program. The aim of this study is to compare the Advanced Skeleton-based animation process with Maya Rig, which can solve the high time-cost rigging problem, and to explore the best automatic plug-in based on the advantages of Advanced Skeleton, broadening the research scope of fish animation.

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Analysis and Recognition of Behavior of Medaka in Response to Toxic Chemical Inputs by using Multi-Layer Perceptron (다층 퍼셉트론을 이용한 유해물질 유입에 따른 송사리의 행동 반응 분석 및 인식)

  • 김철기;김광백;차의영
    • Journal of Korea Multimedia Society
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    • v.6 no.6
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    • pp.1062-1070
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    • 2003
  • In this paper, we observe one of the aquatic insect, fish(Medaka)'s behavior which reacts to giving toxic chemicals until lethal conditions using automatic tracking sl$.$stem. For the result, we define the Pattern A is a normal movement of fish and Pattern B is after giving the chemicals. In order to detect the movement of fish automatically, these patterns are selected for the training data of the artificial neural networks. The average recognition rates of the pattern B are remarkably increased after inputs of toxic chemical(diazinon) while the Pattern A is decreased distinctively. This study demonstrates that artificial neural networks are useful method for detecting presence of toxicoid in environment as for an alternative of in-situ behavioral monitoring tool.

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Development of a Fish-trait Editor for Constructing Cyber Aquarium (사이버 아쿠아리움 구축을 위한 어류속성 편집기 개발)

  • Kang, Gyeong-Heon;Geong, Seung-Moon;Lee, Hyeon-Cheol;Kim, Eun-Seok;Hur, Gi-Taek
    • Proceedings of the Korea Contents Association Conference
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    • 2006.11a
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    • pp.528-532
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    • 2006
  • In a cyber aquarium, the behavior of fish objects is the most important factor in respect of visual effects. In this paper, we analyze the principal habits of fish objects such as the vitality, the range of movement, the maximum depth of water they can live, and the cycle of eating. Then, we suggest a method for simulating the stable marine ecosystem with controlling the behaviors, the interaction with other species, the average span of life, and all that sort of thing based on the result of analysis. Because we can freely modify the behavior of fish object by altering the values of attributes, it can be utilized in the dynamic cyber aquarium, the 3D aquarium screen saver, and the cyber fish game, and so on.

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