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Digital Face Replacement in Photographs

Digital Face Replacement in Photographs. CSC2530F Project Presentation By: Shahzad Malik January 28, 2003. Face Replacement Motivation. Currently done manually by graphic artists using photo editing software An automatic system has many potential uses: Hollywood special effects

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Digital Face Replacement in Photographs

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  1. Digital Face Replacement in Photographs CSC2530F Project Presentation By: Shahzad Malik January 28, 2003

  2. Face Replacement Motivation • Currently done manually by graphic artists using photo editing software • An automatic system has many potential uses: • Hollywood special effects • “Personalized” movies • Framing someone…

  3. Required Components • Need the following subsystems: • Face detection (and tracking for videos) • Head pose estimator • Illumination extractor (*) • Facial expression synthesis • Merging/replacement algorithm (*)

  4. Light Estimation • Assuming a Lambertian reflectance model: • Any image can then be represented by:

  5. Approximate Skin Tone • Cannot assume 3 basis images for arbitrary photographs • Use an approximate image to generate basis

  6. Fitting a Generic 3D Model • Need geometry to create basis images • Fit a generic 3D face mesh to images • “Lift” a texture using planar mapping

  7. Generate Basis Images • Set 3 linearly independent light positions • Relight skin tone model with each light

  8. Determining the Coefficients • Compute a least squares solution to: • Solve separately for each RGB channel

  9. Re-illuminating the Target Face • Set intensities of the 3 light sources to the coefficient values • Render the target face with these lights

  10. Flesh Pixel Detection • Match non-mesh skin pixels to new skin tone • Use a histogram-based skin classifier

  11. Histogram Matching • Generate histograms for newly lit face • Match the Gaussian distribution from original face to newly lit face • For each flesh pixel in original image, choose a new color with a similar location on the Gaussian bell curve

  12. Weighted Color Blending • Blend converted flesh pixels with face mesh pixels

  13. Results

  14. Results (continued)

  15. Results (continued)

  16. Results (continued)

  17. Summary • Presented a face replacement system • Takes lighting and merging into account • Future research areas: • Face detection and tracking (for videos) • Expression synthesis • More sophisticated reflectance model • Automatic and precise model-fitting

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