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Acoustic Art: Revolutionizing The Way You Listen To Pictures Matt Clark (Image Analysis Expert) Jay Davis (Spring Team Lead) Kyle Kearney (Fall Team Lead) Vince Tilanus (Client Liaison) Louis Piano (Client) Will French (Industry Rep., Jive Software) Dr. Karen Ward (Faculty Advisor)
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Introduction Music out of images Beau Lotto (TED Talk) Visuals in sound therapy Beau Lotto: Optical illusions show -how we see Beau Lotto: Optical illusions show -how we see - Oct 2009. Ted.com
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Why? Take an idea a step further Novel concept Combining abstract ideas Microsoft Imagine Cup
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Image As Blocks
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Design: Image analysis Edge Detection-Sobel Edge Detection Texture Analysis- Haar wavelet (Discrete Wavelet Transform) Dominant Color-most common color (mode) Average Brightness-average all pixels (mean) (Sobel, 1991)
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Life After Edge Detection
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Design: Image analysis Edge Detection-Sobel Edge Detection Texture Analysis- Haar wavelet (Discrete Wavelet Transform) Dominant Color-most common color (mode) Average Brightness-average all pixels (mean) (Sobel, 1991)
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Texture Analysis
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Design: Image analysis Edge Detection-Sobel Edge Detection Texture Analysis- Haar wavelet (Discrete Wavelet Transform) Dominant Color-most common color (mode) Average Brightness-average all pixels (mean)
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Dominant Color and Average Brightness
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Design: Music Generation Take input from image analysis. Configurable instruments-user can edit and composer will use. Multiple composers. o Naive Pentatonic o Music Theoretical
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Naïve Pentatonic Composer Just brightness Pentatonic scale o Guaranteed to have notes not clash
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Music Theoretical Composer Apply basic music theory. Use all available image characteristics Generate: o Rhythm o Melody o Counter-melody o Harmony o Bassline o Volume o Scale o Key Change
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Demonstration
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Accomplishments Combined two forms of creative expression o Visual Art o Music Created a complex algorithm from scratch
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Conclusion What next? o MTC updates and modifications o GUI progress display o Next year senior project?
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Questions?
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