  Delivering immersive, 3D experiences for human communication requires a
method to obtain 360 degree photo-realistic avatars of humans. To make these
experiences accessible to all, only commodity hardware, like mobile phone
cameras, should be necessary to capture the data needed for avatar creation.
For avatars to be rendered realistically from any viewpoint, we require
training images and camera poses from all angles. However, we cannot rely on
there being trackable features in the foreground or background of all images
for use in estimating poses, especially from the side or back of the head. To
overcome this, we propose a novel landmark detector trained on synthetic data
to estimate camera poses from 360 degree mobile phone videos of a human head
for use in a multi-stage optimization process which creates a photo-realistic
avatar. We perform validation experiments with synthetic data and showcase our
method on 360 degree avatars trained from mobile phone videos.
