政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/150265
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文笔数/总笔数 : 113311/144292 (79%)
造访人次 : 50918904      在线人数 : 819
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻


    请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/150265


    题名: 《幻意視界》- 以生成式藝術與眼動追蹤技術探討意識的變幻
    《Illusory Eyescape》- Exploring the Variations of Consciousness through Generative Art and Eye-Tracking Techniques
    作者: 李欣霏
    Lee, Sin-Fei
    贡献者: 紀明德
    陶亞倫
    Chi, Ming-Te
    Tao, Ya-Lun
    李欣霏
    Lee, Sin-Fei
    关键词: 生成式藝術
    眼動追蹤
    互動式藝術
    日期: 2024
    上传时间: 2024-03-01 14:13:35 (UTC+8)
    摘要: 在科技的洪流中，藝術形式與數位技術不斷交融、適應、演變，從機械複製時代到虛擬再現真實，到現在連生成作品的工作都變成一句咒語就能夠解決的事，那麼究竟藝術創作的本質到底是甚麼?瑞士藝術家阿爾伯托·賈科梅蒂（Alberto Giacometti）曾說：「藝術品不是再現真實，而是創造具有相同強度的真實。」在此，藝術作品僅作為表達真實感受的一種媒介，其本質在於超出物性所展現出無形的精神與情感。
    因此本論文旨在利用科技藝術創作的方式來探討人與機器的意識差異，以及透過生成式人工智慧來呈現藝術作品的本質，同時，我們也將關注語言在藝術創作中的限制。在創作過程中經由文獻探討梳理想法，咀嚼吸收後成為創作的養分，最終進行作品展覽，與觀眾合力完成作品。
    作品以眼動儀追蹤獲取觀眾意識的視覺資訊做為生成式人工智慧的輸入，並根據輸入產出畫作後顯現。利用各種視覺意象如：觀者的眼睛、眼動追蹤、致敬比利時藝術家雷內·馬格利特畫作「虛假的鏡子」等等，象徵人類的存在和自由以及討論主觀和客觀等意義。創作作品須透過觀眾親自體驗的過程來感受人類「意識」的重要性。
    參考文獻: [1] E. Mansimov, E. Parisotto, J. L. Ba, and R. Salakhutdinov, “Generating images
    from captions with attention,” arXiv preprint arXiv:1511.02793, 2015.
    [2] P. Wolfendale, Object-oriented philosophy: The noumenon’s new clothes. MIT
    Press, 2019, vol. 1.
    [3] M. Coeckelbergh, “Can machines create art?” Philosophy & Technology, vol. 30,
    no. 3, pp. 285–303, 2017.
    [4] J.-W. Hong and N. M. Curran, “Artificial intelligence, artists, and art: attitudes
    toward artwork produced by humans vs. artificial intelligence,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM),
    vol. 15, no. 2s, pp. 1–16, 2019.
    [5] E. S. Mikalonytė and M. Kneer, “Can artificial intelligence make art?: Folk intuitions as to whether ai-driven robots can be viewed as artists and produce art,”
    ACM Transactions on Human-Robot Interaction (THRI), vol. 11, no. 4, pp. 1–19,
    2022.
    [6] A. Ramesh, M. Pavlov, G. Goh, S. Gray, C. Voss, A. Radford, M. Chen, and
    I. Sutskever, “Zero-shot text-to-image generation,” pp. 8821–8831, 2021.
    [7] G. M. Edelman, Neural Darwinism: The theory of neuronal group selection. Basic books, 1987.
    [8] G. M. Edelman and G. Tononi, A universe of consciousness: How matter becomes
    imagination. Hachette UK, 2008.
    [9] 傑拉爾德·M·埃德爾曼、朱利歐·托諾尼, 意識的宇宙：物質如何轉變
    為精神（重譯版）, 2019.
    [10] G. Tononi, “An information integration theory of consciousness,” BMC neuroscience, vol. 5, pp. 1–22, 2004.
    [11] A. Haun and G. Tononi, “Why does space feel the way it does? towards a principled account of spatial experience,” Entropy, vol. 21, no. 12, p. 1160, 2019.
    [12] B. J. Baars, A cognitive theory of consciousness. Cambridge University Press,
    1993.
    [13] ——, “Global workspace theory of consciousness: toward a cognitive neuroscience of human experience,” Progress in brain research, vol. 150, pp. 45–53,
    2005.
    [14] S. Dehaene, M. Kerszberg, and J.-P. Changeux, “A neuronal model of a global
    workspace in effortful cognitive tasks,” Proceedings of the national Academy of
    Sciences, vol. 95, no. 24, pp. 14 529–14 534, 1998.
    [15] R. VanRullen and R. Kanai, “Deep learning and the global workspace theory,”
    Trends in Neurosciences, vol. 44, no. 9, pp. 692–704, 2021.
    [16] N. Block, “How many concepts of consciousness?” Behavioral and brain sciences, vol. 18, no. 2, pp. 272–287, 1995.
    [17] K. Xu, J. Ba, R. Kiros, K. Cho, A. Courville, R. Salakhudinov, R. Zemel, and
    Y. Bengio, “Show, attend and tell: Neural image caption generation with visual
    attention,” pp. 2048–2057, 2015.
    [18] O. Vinyals, A. Toshev, S. Bengio, and D. Erhan, “Show and tell: A neural image
    caption generator,” pp. 3156–3164, 2015.
    [19] K. Gregor, I. Danihelka, A. Graves, D. Rezende, and D. Wierstra, “Draw: A
    recurrent neural network for image generation,” pp. 1462–1471, 2015.
    [20] A. Mordvintsev, C. Olah, and M. Tyka, “Inceptionism: Going deeper into neural
    networks,” 2015.
    [21] L. A. Gatys, A. S. Ecker, and M. Bethge, “A neural algorithm of artistic style,”
    arXiv preprint arXiv:1508.06576, 2015.
    [22] J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros, “Unpaired image-to-image translation
    using cycle-consistent adversarial networks,” pp. 2223–2232, 2017.
    [23] T. Karras, S. Laine, and T. Aila, “A style-based generator architecture for generative adversarial networks,” pp. 4401–4410, 2019.
    [24] J. Ho, A. Jain, and P. Abbeel, “Denoising diffusion probabilistic models,” Advances in neural information processing systems, vol. 33, pp. 6840–6851, 2020.
    [25] A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry,
    A. Askell, P. Mishkin, J. Clark et al., “Learning transferable visual models from
    natural language supervision,” pp. 8748–8763, 2021.
    [26] R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer, “High-resolution
    image synthesis with latent diffusion models,” pp. 10 684–10 695, 2022.
    [27] L. Wittgenstein and R. Monk, Tractatus logico-philosophicus. Routledge, 2013.
    [28] M. O’Sullivan, An Analysis of Ludwig Wittgenstein’s Philosophical Investigations. Macat Library, 2017.
    [29] T. Nagel, “What is it like to be a bat?” pp. 159–168, 1980.
    [30] G. Morrot, F. Brochet, and D. Dubourdieu, “The color of odors,” Brain and language, vol. 79, no. 2, pp. 309–320, 2001.
    [31] G. Harman, Object-oriented ontology: A new theory of everything. Penguin
    UK, 2018.
    [32] E. Husserl, Cartesian meditations: An introduction to phenomenology. Springer
    Science & Business Media, 2013.
    [33] A. Papoutsaki, P. Sangkloy, J. Laskey, N. Daskalova, J. Huang, and J. Hays,
    “Webgazer: Scalable webcam eye tracking using user interactions,” in Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI).
    AAAI, 2016, pp. 3839–3845.
    [34] 大學入學考試中心研究發展處, “高中英文參考詞彙表,” https://www.ceec.
    edu.tw/SourceUse/ce37/ce37.htm.
    [35] K. Rayner, “Eye movements in reading and information processing: 20 years of
    research.” Psychological bulletin, vol. 124, no. 3, p. 372, 1998.
    [36] T. Mikolov, K. Chen, G. Corrado, and J. Dean, “Efficient estimation of word
    representations in vector space,” arXiv preprint arXiv:1301.3781, 2013.
    [37] Q. Le and T. Mikolov, “Distributed representations of sentences and documents,”
    in International conference on machine learning. PMLR, 2014, pp. 1188–1196.
    描述: 碩士
    國立政治大學
    數位內容碩士學位學程
    110462008
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0110462008
    数据类型: thesis
    显示于类别:[數位內容碩士學位學程] 學位論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    200801.pdf39491KbAdobe PDF0检视/开启


    在政大典藏中所有的数据项都受到原著作权保护.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈