The recent advances in visual data acquisition and consumption
have led to the emergence of the so-called plenoptic visual models,
where Point Clouds (PCs) are playing an increasingly important
role. Point clouds are a 3D visual model where the visual scene is
represented through a set of points and associated attributes, notably
color. To offer realistic and immersive experiences, point clouds
need to have millions, or even billions, of points, thus asking for
efficient representation and coding solutions. This is critical for
emerging applications and services, notably virtual and augmented
reality, personal communications and meetings, education and
medical applications and virtual museum tours. The point cloud
coding field has received many contributions in recent years,
notably adopting deep learning-based approaches, and it is critical
for the future of immersive media experiences. In this context, the
key objective of this tutorial is to review the most relevant point
cloud coding solutions available in the literature with a special focus
on deep learning-based solutions and its specific novel features.
Special attention will be dedicated to the ongoing standardization
projects in this domain, notably in JPEG and MPEG.