Publikation
CONFIDENCE-AWARE CLUSTERED LANDMARK FILTERING FOR HYBRID 3D FACE TRACKING
Jilliam Maria Diaz Barros; Chen-Yu Wang; Didier Stricker; Jason Raphael Rambach
In: IEEE (Hrsg.). Proceedings of the 30th ICIP. IEEE International Conference on Image Processing (ICIP-2023), October 8-11, Kuala Lumpur, Malaysia, IEEE, 2023.
Zusammenfassung
The detection of facial landmarks in 2D images has received
a great attention in the last decade, as it is a key step for
several computer-vision-related applications. Most of the
approaches are focused on still images, and are extended
to videos by using a tracking-by-detection scheme. In this
work, we propose a frame-to-frame tracking module based on
grouped-landmark Kalman filters that can be integrated into
existing deep-learning-based 3D face alignment pipelines.
This method improves the landmark accuracy in cases with
large occlusion, extreme head poses and blurriness that affect
existing approaches. Our experiments on the Menpo
3DA-2D benchmark show improvements on model-free and
3D-model-based face alignment approaches.