  In this paper, we propose an automatic approach for localizing the inner eye
canthus in thermal face images. We first coarsely detect 5 facial keypoints
corresponding to the center of the eyes, the nosetip and the ears. Then we
compute a sparse 2D-3D points correspondence using a 3D Morphable Face Model
(3DMM). This correspondence is used to project the entire 3D face onto the
image, and subsequently locate the inner eye canthus. Detecting this location
allows to obtain the most precise body temperature measurement for a person
using a thermal camera. We evaluated the approach on a thermal face dataset
provided with manually annotated landmarks. However, such manual annotations
are normally conceived to identify facial parts such as eyes, nose and mouth,
and are not specifically tailored for localizing the eye canthus region. As
additional contribution, we enrich the original dataset by using the annotated
landmarks to deform and project the 3DMM onto the images. Then, by manually
selecting a small region corresponding to the eye canthus, we enrich the
dataset with additional annotations. By using the manual landmarks, we ensure
the correctness of the 3DMM projection, which can be used as ground-truth for
future evaluations. Moreover, we supply the dataset with the 3D head poses and
per-point visibility masks for detecting self-occlusions. The data will be
publicly released.
