Title: A Hybrid Approach to Video Source Identification,
Abstract: Multimedia Forensics allows to determine whether videos or images have been
captured with the same device, and thus, eventually, by the same person.
Currently, the most promising technology to achieve this task, exploits the
unique traces left by the camera sensor into the visual content. Anyway, image
and video source identification are still treated separately from one another.
This approach is limited and anachronistic if we consider that most of the
visual media are today acquired using smartphones, that capture both images and
videos. In this paper we overcome this limitation by exploring a new approach
that allows to synergistically exploit images and videos to study the device
from which they both come. Indeed, we prove it is possible to identify the
source of a digital video by exploiting a reference sensor pattern noise
generated from still images taken by the same device of the query video. The
proposed method provides comparable or even better performance, when compared
to the current video identification strategies, where a reference pattern is
estimated from video frames. We also show how this strategy can be effective
even in case of in-camera digitally stabilized videos, where a non-stabilized
reference is not available, by solving some state-of-the-art limitations. We
explore a possible direct application of this result, that is social media
profile linking, i.e. discovering relationships between two or more social
media profiles by comparing the visual contents - images or videos - shared
therein.