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Pattern-Based Texture Metamorphosis by Z. Liu, C. Liu, and H. Shum

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Explore the complexities of image morphing versus texture morphing, focusing on pattern distribution, correspondence establishment, and smooth warp field generation. This study introduces a novel approach for pattern detection, alignment, and blending, minimizing morphing path gaps for enhanced texture transformation.

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Pattern-Based Texture Metamorphosis by Z. Liu, C. Liu, and H. Shum

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  1. Pattern-based Texture Metamorphosis Z. Liu, C. Liu, and H. Shum Microsoft Research Asia Y. Yu UIUC

  2. Image Morphing vs. Texture Morphing Image Morphing • Specify Features and Correspondence * • Warp Generation • Transition Control * Require a lot of human intervention

  3. Image Morphing vs. Texture Morphing Texture Morphing • Textures are usually homogenous with features everywhere. • Hard to specify features • Hard to build correspondence

  4. Direct Blending Does Not Work source target Random Semi-structured Regular

  5. Interesting Problems In Texture Morphing • What pair of textures? • Similar and repeatable patterns. • Pattern distributions are alike. • What is the feature? • User define pattern. • How to extract so many patterns? • Semi-automatic approach. • How to build correspondence? • Generate a smooth warp field.

  6. Our Approach • 1. Pattern Detection and Alignment • 2. Establishing Correspondence • 3. Warping and Blending Source texture Target texture Morphing sequence

  7. Pattern Representation & Distance Measurement • Pattern Representation • Shape Distance • Local Feature Distance

  8. Pattern Detection & Alignment • Step1: Initialization by Generalized Hough Transform (GHT). • Step2: Alignment by top-down verification. • Step3: Refinement by human intervention.

  9. Step1: Initialization Pattern Detection & Alignment Original texture Voting of a pixel User selected pattern Intensity image Local maximum

  10. Step2: Alignment Pattern Detection & Alignment • (a) Independently update each landmark • (b) Update shape • Iteratively do (a) and (b).

  11. Alignment Process GHT initialization alignment alignment

  12. Pattern Detection & Alignment Step3: Refinement • (a) False detection • (b) False alignment • (c) More than one types of pattern

  13. Correspondence by Minimizing Morphing Path

  14. Warping and Blending From S.Lee

  15. More Results source target Pattern selected

  16. Discussion • About Pattern Selection • Can be any shape • User is responsible • About Correspondence and Transition Control • Problem of crowd patterns • About Warp Generation • MFFD vs. “as rigid as possible”

  17. Thank you !

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