Authors:
Ahmed Rekik
1
;
Achraf Ben-Hamadou
2
and
Walid Mahdi
1
Affiliations:
1
Sfax University, Tunisia
;
2
Total Immersion SA, France
Keyword(s):
3D Face Tracking, RGB-D Cameras, Lighting Condition Changes, Augmented Reality, Human Computer Interaction.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Enterprise Information Systems
;
Human and Computer Interaction
;
Human-Computer Interaction
;
Motion, Tracking and Stereo Vision
;
Tracking and Visual Navigation
Abstract:
This paper presents a new method for 3D face pose tracking in arbitrary illumination change conditions using
color image and depth data acquired by RGB-D cameras (e.g., Microsoft Kinect, Asus Xtion Pro Live, etc.).
The method is based on an optimization process of an objective function combining photometric and geometric
energy. The geometric energy is computed from depth data while the photometric energy is computed at each
frame by comparing the current face texture to its corresponding in the reference face texture defined in
the first frame. To handle the effect of changing lighting condition, we use a facial illumination model in
order to solve which lighting variations has to be applied to the current face texture making it as close as
possible to the reference texture. We demonstrate the accuracy and the robustness of our method in normal
lighting conditions by performing a set of experiments on the Biwi Kinect head pose database. Moreover,
the robustness to illumination chang
es is evaluated using a set of sequences for different persons recorded in
severe lighting condition changes. These experiments show that our method is robust and precise under both
normal and severe lighting conditions.
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