Content-Based Multimedia Copy Detection

Abstract

In this paper, we address the problem of multimedia content-based copy detection. We propose several audio and video fingerprints that are highly robust to audio and video transformations. We propose to accelerate the search of fingerprints by using a Graphics Processing Unit (GPU). To speedup this search even further, we propose a two-step search based on a clustering technique and a lookup table that reduces the number of comparisons between the query and the reference fingerprints. We evaluate our fingerprints on the well-known TRECVID 2009 and 2010 datasets, and we show that the proposed fingerprints outperform other state-of-the-art audio and video fingerprints while being significantly faster.