  We propose an automatic video inpainting algorithm which relies on the
optimisation of a global, patch-based functional. Our algorithm is able to deal
with a variety of challenging situations which naturally arise in video
inpainting, such as the correct reconstruction of dynamic textures, multiple
moving objects and moving background. Furthermore, we achieve this in an order
of magnitude less execution time with respect to the state-of-the-art. We are
also able to achieve good quality results on high definition videos. Finally,
we provide specific algorithmic details to make implementation of our algorithm
as easy as possible. The resulting algorithm requires no segmentation or manual
input other than the definition of the inpainting mask, and can deal with a
wider variety of situations than is handled by previous work. 1. Introduction.
Advanced image and video editing techniques are increasingly common in the
image processing and computer vision world, and are also starting to be used in
media entertainment. One common and difficult task closely linked to the world
of video editing is image and video " inpainting ". Generally speaking, this is
the task of replacing the content of an image or video with some other content
which is visually pleasing. This subject has been extensively studied in the
case of images, to such an extent that commercial image inpainting products
destined for the general public are available, such as Photoshop's " Content
Aware fill " [1]. However, while some impressive results have been obtained in
the case of videos, the subject has been studied far less extensively than
image inpainting. This relative lack of research can largely be attributed to
high time complexity due to the added temporal dimension. Indeed, it has only
very recently become possible to produce good quality inpainting results on
high definition videos, and this only in a semi-automatic manner. Nevertheless,
high-quality video inpainting has many important and useful applications such
as film restoration, professional post-production in cinema and video editing
for personal use. For this reason, we believe that an automatic, generic video
inpainting algorithm would be extremely useful for both academic and
professional communities.
