Adaptive division of feature space for rapid detection of near-duplicate video segments

Near-duplicate video detection is becoming a core-technology for analyzing the structure of a large-scale video archive. It, however, is naturally an O(n2 ) problem, where n is a value proportional to the total length of an input video stream. We have previously challenged this time-consuming task by reducing the cost required for each of the O(n2 ) comparisons. This paper, on the other hand, proposes a method that reduces the number of comparisons by adaptively dividing the feature space according to the distribution of feature points.

• Type: Journal
• Year: 2009
• Where: ICMCS
• Authors: Ichiro Ide, Shugo Suzuki, Tomokazu Takahashi, Hiroshi Murase
• Keywords: ICMCS 2009, Input Video Stream, Large-scale Video Archive, Multimedia, Near-duplicate Video Detection