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The wild world of web also allows users to easily share visual contents through social media platforms. Images and videos are used to convey persuasive messages to be used under several different environments, from propaganda to child pornography. In the last decades, visual data gained a key role in providing information. VISION can be exploited as benchmark for the exhaustive evaluation of several image and video forensic tools.
How to change logitech camera settings to save as .mov portable#
The VISION dataset is currently composed by 34,427 images and 1914 videos, both in the native format and in their social version (Facebook, YouTube, and WhatsApp are considered), from 35 portable devices of 11 major brands. The goal of this paper is to propose the VISION dataset as a contribution to the development of multimedia forensics.
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On the other hand, portable devices capture both images and videos with the same sensor, opening new forensic opportunities. These facts pose new challenges to the forensic community: for example, most modern cameras feature digital stabilization, that is proved to severely hinder the performance of video source identification technologies moreover, the strong re-compression enforced by SMPs during upload threatens the reliability of multimedia forensic tools.
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Remarkably, in the latest years, portable devices became the preferred means to capture images and videos, and contents are commonly shared through social media platforms (SMPs, for example, Facebook, YouTube, etc.). However, the performance of proposed tools are usually tested on data that are far from reality in terms of resolution, source device, and processing history. Forensic research community keeps proposing new techniques to analyze digital images and videos.