DISTRIBUTED VIDEO IDENTIFICATION WITH PERCEPTUAL TAGS IN PEER-TO-PEER NETWORKS

Year 2018, Volume: 19 Issue: 1, 132 - 143, 31.03.2018

Alper Koz

https://doi.org/10.18038/aubtda.330958

Abstract

Existing methods in Peer-to-Peer (P2P)
networks mainly use file tags or cryptographic hashes of the entire file for
video searching and identification. These methods however become insufficient
to correctly identify a video when the name and format of the files are
changed. In this paper, a distributed solution is proposed for video
identification and copy detection in P2P networks, which represents a video file
in the network with a set of (64-256) bits, named as perceptual tags. As such
information is derived from the perceptual content of the video rather than its
bitstream representation as in the case of cryptographic hashes, it provides a
robust identification after the alterations in the file names and formats provided
that the visual quality of the video is at acceptable levels. The paper first
briefly discusses the requirements for a distributed perceptual tagging system
considering the low computational power and low bandwidth of internet users.
Then, it presents the proposed perceptual tag extraction method using the
temporal differences between the video frame averages and the proposed
distributed searching scheme for a P2P implementation. The proposed extraction
and searching methods provide robustness to the alterations in video formats
and small additions and cuttings in the video content as the typical processing
in P2P environment and also achieve uniform distribution and storage load
between the peers.

Keywords

Perceptual tags, peer to peer networks, content search, distributed video identification, distributed hash tables

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