Fast Near-Duplicate Video Retrieval via Motion Time Series Matching

Abstract

This paper introduces a method for the efficient comparison and retrieval of near duplicates of a query video from a video database. The method generates video signatures from histograms of orientations of optical flow of feature points computed from uniformly sampled video frames concatenated over time to produce time series, which are then aligned and matched. Major incline matching, a data reduction and peak alignment method for time series, is adapted for faster performance. The resultant method is compact and robust against a number of common transformations including: flipping, cropping, picture-in-picture, photometric, addition of noise and other artifacts. We evaluate on the MUSCLE VCD 2007 dataset and a dataset derived from TRECVID 2009. Good precision (average 88.8%) at significantly higher speeds (average durations: 45 seconds for signature generation plus 92 seconds for a linear search of 81-second query video in a 300 hour dataset) than results reported in the literature are shown.