Near-duplicate video detection
Detection of duplicate or near-duplicate videos on large-scale
database plays an important role in video search. In this
paper, we analyze the problem of near-duplicates detection
and propose a practical and eective solution for real-time
large-scale video retrieval. Unlike many existing approaches
which make use of video frames or key-frames, our solution is based on a more discriminative signature of video
clips. The feature used in this paper is an extension of ordinal measures which have proven to be robust to change
in brightness, compression formats and compression ratios.
For ecient retrieval, we propose to use Multi-Probe Locality Sensitive Hashing (MPLSH) to index the video clips for
fast similarity search and high recall. MPLSH is able to filter
out a large number of dissimilar clips from video database.
To refine the search process, we apply a slightly more expensive clip-based signature matching between a pair of videos.
Experimental results on the data set of 12,790 videos
show that the proposed approach achieves at least 6.5% average precision improvement over the baseline color histogram
approach while satisfying real-time requirements. Furthermore, our approach is able to locate the frame oset of copy
segment in near-duplicate videos.