Video copy detection by fast sequence matching

Sequence matching techniques are effective for comparing two videos. However, existing approaches suffer from demanding computational costs and thus are not scalable for large-scale applications. In this paper we view video copy detection as a local alignment problem between two frame sequences and propose a two-level filtration approach which achieves significant acceleration to the matching process. First, we propose to use an adaptive vocabulary tree to index all frame descriptors extracted from the video database. In this step, each video is treated as a “bag of frames.” Such an indexing structure not only provides a rich vocabulary for representing videos, but also enables efficient computation of a pyramid matching kernel between videos. This vocabulary tree filters those videos that are dissimilar to the query based on their histogram pyramid representations. Second, we propose a fast edit-distance-based sequence matching method that avoids unnecessary comparisons between d...

• Type: Conference
• Year: 2009
• Where: CIVR
• Authors: Mei-Chen Yeh, Kwang-Ting Cheng
• Keywords: CIVR 2009, Multimedia, Sequence Matching Techniques, Video Copy Detection, Vocabulary Tree