  One of the key research areas in computer vision addressed by a vast number
of publications is the processing and understanding of images containing human
faces. The most often addressed tasks include face detection, facial landmark
localization, face recognition and facial expression analysis. Other, more
specialized tasks such as affective computing, the extraction of vital signs
from videos or analysis of social interaction usually require one or several of
the aforementioned tasks that have to be performed. In our work, we analyze
that a large number of tasks for facial image processing in thermal infrared
images that are currently solved using specialized rule-based methods or not
solved at all can be addressed with modern learning-based approaches. We have
used USTC-NVIE database for training of a number of machine learning algorithms
for facial landmark localization.
