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94 lines
5.1 KiB
94 lines
5.1 KiB
<!DOCTYPE html>
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<meta charset="UTF-8">
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<meta name="og:description" content="Cailean Finn's Garden (ง•_•)ง Artist * Creative Technologist" />
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<meta name="description" content="Cailean Finn's Garden (ง•_•)ง Artist * Creative Technologist" />
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<meta content="Beta Festival 2024" property="og:title"/>
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<meta name="keywords" content="cailean finn, new media, art and technology, digital art" />
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<title>cailean.finn</title>
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<body>
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<div id="main-container">
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<div id="nav-container">
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<div class="nav-emoji">
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<a href="/"><div class="emoji-flip">(ง•_•)ง</div></a>
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<div class="nav-about"><a href="/about">cailean.finn</a></div>
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<div class="nav-emoji"><a href="/list">projects</a></div>
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<div class="nav-emoji"><a href='/gallery'>gallery</a></div>
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<div id="container">
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<div id="project-container">
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<div id="project-header">Stubborn Vectors, 2024</div>
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<div id="project-tags">
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<div class="project-tag">✳ Affetcion Mapping</div>
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<div class="project-tag">✳ AI</div>
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<div class="project-tag">✳ Embedded Computing</div>
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</div>
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<div id="project-cover">
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<img src="/images/sv-image.webp">
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<div id="project-body">
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<p>Stubborn Vectors is an interactive installation that explores the computational gaze of computer vision systems, which often oversimplify the complexities of our corporeal selves.</p>
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<p>Computer vision is deeply entwined with surveillance technologies, accelerating the extraction of information to classify, analyse, and predict human behaviours—often capturing far more than individuals intend to reveal. This work focuses on Affection Mapping, a branch of machine learning dedicated to classifying emotions using computer vision. However, emotions are complex, evolving in response to our families, environments, and personal histories. This inherent complexity exposes the limitations of models attempting to construct a rigid taxonomy of human emotion.</p>
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<p>In their pursuit to classify and represent the physical world, these systems inadvertently reveal an unfamiliar umwelt—a new lens through which meaning is extracted and reality is interpreted. By examining this computational gaze, we can observe how these systems function, their inherent biases, and how they influence and bleed into our physical world.</p>
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<p>The installation is built as a computational system composed of computer vision and machine learning models. A dataset of archived footage is processed through this system to detect, segment, and extract features from each frame, with each feature represented as a multi-dimensional vector or embedding. This data is then sorted, reduced in dimensionality, and mapped into a two-dimensional space, creating a human-readable representation of the system's latent space. Using custom-built controllers, users can query the system with an emotional state, prompting it to navigate toward its nearest embedding within the space.</p>
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<p><img alt="sv-install" src="/images/stubborn-vectors/install-sv.jpg" title="sv install" /></p>
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<p><img alt="sv-install" src="/images/stubborn-vectors/install-sv-2.jpg" title="sv install" /></p>
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<p><img alt="sv-install" src="/images/stubborn-vectors/controller-emote.jpg" title="sv install" /></p>
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<p><img alt="sv-install" src="/images/stubborn-vectors/wip-sv-1.png" title="sv install" /></p>
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<p><img alt="sv-install" src="/images/stubborn-vectors/cailean-finn-beta-wip-1.jpg" title="sv install" /></p>
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<p><img alt="sv-install" src="/images/stubborn-vectors/cailean-finn-beta-wip-3.jpg" title="sv install" /></p>
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<p><img alt="sv-install" src="/images/stubborn-vectors/IMG_1234.jpg" title="sv install" /></p>
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<p><img alt="sv-install" src="/images/stubborn-vectors/IMG_1252.jpg" title="sv install" /></p>
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<p><img alt="sv-install" src="/images/stubborn-vectors/some-text.png" title="sv install" /></p>
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<div id="project-showcase">
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<div id="pr-header">Exhibited:</div>
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<div id="showcase-cont">
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<div class="showcase">
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<p>(2024)
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Beta Festival,
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Dublin</p>
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</div>
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</div>
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<div id="modified-time">
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<h4>Last Modified: </h4>
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<p> Mon Nov 4 15:06:45 2024</p>
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