Face Tracking?

I tried your program for face tracking.

First, I assumed that one single image is given continuously like a video.
At the first frame, the alignment was successful because it starts with the mean shape.

But the problem happens from the second frame.
After the first frame, current shape is almost close to the ground truth.
The first stage of regressor is trained with the mean shape and augmented data.
Then, the result of regressor contains large displacement from the ground truth.
Therefore, At the second frame, the shape moves largely by first stage of regressor.
As the frame goes, shape diverges smoothly.

Somebody suggests to start with the mean shape at each frame.
But it sometimes fails if face is rotated largely.

Therefore, I think starting with the previous frame's shape is the best way.

Do you have any experience of idea about this problem of face tracking?

The issue names no files, tests, or entry points. Start by locating the MATLAB face-tracking flow and compare mean-shape initialization with previous-frame initialization across consecutive and highly rotated frames; done means the chosen initialization avoids landmark divergence without losing rotated-face cases.

Written by the indexing model from the issue text.