Live Video Forensics: Source Identification
in Lossy Wireless Networks
Abstract— Video source identification is very important in validating video evidence, tracking down video piracy crimes, and regulating individual video sources. With the prevalence of wireless communication, wireless video cameras continue to replace their wired counterparts in security/surveillance systems and tactical networks. However, wirelessly streamed videos usually suffer from blocking and blurring due to inevitable < Final Year Projects 2016 > unavoidable packet loss in wireless transmissions. The existing source identification methods experience significant performance degradation or even fail to work when identifying videos with blocking and blurring. We propose a method that is effective and efficient in identifying such wirelessly streamed videos. In addition, we also propose to incorporate wireless channel signatures and selective frame processing into source identification, which significantly improve the identification speed.
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