  MOBIO is a bi-modal database that was captured almost exclusively on mobile
phones. It aims to improve research into deploying biometric techniques to
mobile devices. Research has been shown that face and speaker recognition can
be performed in a mobile environment. Facial landmark localization aims at
finding the coordinates of a set of pre-defined key points for 2D face images.
A facial landmark usually has specific semantic meaning, e.g. nose tip or eye
centre, which provides rich geometric information for other face analysis tasks
such as face recognition, emotion estimation and 3D face reconstruction. Pretty
much facial landmark detection methods adopt still face databases, such as
300W, AFW, AFLW, or COFW, for evaluation, but seldomly use mobile data. Our
work is first to perform facial landmark detection evaluation on the mobile
still data, i.e., face images from MOBIO database. About 20,600 face images
have been extracted from this audio-visual database and manually labeled with
22 landmarks as the groundtruth. Several state-of-the-art facial landmark
detection methods are adopted to evaluate their performance on these data. The
result shows that the data from MOBIO database is pretty challenging. This
database can be a new challenging one for facial landmark detection evaluation.
