CS194-26 Project 4

Face Morphing

Morphing Algorithm:

1. Manually define the correspondence points of each image. Make sure to select the four corners of the image or the triangulation would not include the areas outside of the face!
2. Find the average of the two sets of correspondence points. Perform Delaunay Triangulation of this new set of points.
3. Now we have a list of target triangles. For each target triangle, we compute the affine transformation matrix to warp a source triangle to the target triangle. For each point in the target triangle (calculated by calling scipy's handy function draw.polygon), we apply the inverse affine transform to each point to get the source point. Since the source point could fall between points, we use interp2d to get the weighted average of pixel intensities. Finally, copy this interpolated value back into the target image.
4. Since we want 45 frames, define our step size to 1/45. For t=0..1, step=1/45, compute the average shape at t by following the equation imHalfway = (1-t) * im1 + t * im2. The midway face is the result of t=0.5, where we get exactly half of each image.

Morph 1: Two Danish scientists

Morph 2: Me and Constance Wu

Caricature

Implementation:

Taking the previously computed average Danish computer scientist's Face (call this A), I subtract the correspondence points of my own face (call this B) from the points of A to find the feature differences. We can then use these feature differences to produce a caricature by extrapolating from the mean using the equation: caricature_pts = A + alpha * (B - A), where alpha is greater than 1.

Results