1. Facial Expression Editing in Video Using a Temporally-Smooth Factorization. 2. Face Swapping: Automatically Replacing Faces in Photographs. Facial Expression Editing in Video Using a Temporally-Smooth Factorization.
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1. Facial Expression Editing in Video Using a Temporally-Smooth Factorization
2. Face Swapping: Automatically Replacing Faces in Photographs
Facial Expression Editing in Video Using a Temporally-Smooth Factorization
FeiYang, LubomirBourdev, Eli Shechtman, JueWang, DimitrisMetaxas
The goal is to allow for semantic-level editing of
expressions in a video:
3D Tensor Model
- [Vlasic et al siggraph05]
goal to identify a and
2D v.s. 3D
Weak Projective Matrix Rt
Minimize: | – |
Shape Distribution Constraint:
Adjust to achieve expression modification
Face Swapping: Automatically Replacing Faces in Photographs
Dmitri BitoukNeeraj Kumar SamreenDhillon Peter Belhumeur Shree K. Nayar
For an input image:
OKAO face detector to detect face pose [Omron07]
Pose, Resolution, and Image Blur:
To ensure the similarity between the replaced and original face, a linear combination of 9 spherical harmonics [Ramamoorthi and Hanrahan 2001; Basri and Jacobs 2003] is used as measure metric:
Each pixel I(x, y) can be approximated by:
256-by-256 patch from the face is used for replacement.
L2 Norm is used to compute the distance
Using simple scaling on the Harmonics coefficients
, are the original and replacement images
Scale the replaced image
Any Questions ?