Medusa: 4D face reconstruction and analysis
Medusa: 4D face reconstruction and analysis#
Medusa is a Python toolbox to perform 4D face reconstruction and analysis. You can use it to reconstruct a series of 3D meshes of (moving) faces from video files: one 3D mesh for each frame of the video (resulting in a “4D” representation of facial movement). In addition to functionality to reconstruct faces, Medusa also contains functionality to preprocess and analyze the resulting 4D reconstructions.
When (not) to use Medusa?#
Medusa allows you to reconstruct, preprocess, and analyze frame-by-frame time series of 3D faces from videos. The data that Medusa outputs is basically a set of 3D points (“vertices”), which together represent face shape, that move over time. Medusa then processes these points in a similar way that fMRI or EEG/MEG software processes voxels or sensors, but instead of representing “brain activity”, it represents face movement! Medusa makes relatively few assumptions as to how you want to (further) analyze the face and just returns the raw set of vertices. For some ideas on how to analyze such data, check out the analysis tutorials.
If you just want to perform face detection, pose estimation, or want to extract high-level properties such as action units or categorical emotions, check out the awesome Py-Feat Python package.
A great way to get more familiar with the package is to check out the quickstart!