Classification of Near-Duplicate Video Segments Based on Their Appearance Patterns
Ichiro Ide, Yuji Shamoto, Daisuke Deguchi, Tomokazu Takahashi, Hiroshi Murase · 2010
We propose a method that analyzes the structure of a large volume of general broadcast video data by the appearance patterns of near-duplicate video segments. We define six classification rules based on the appearance patterns of near-duplicate video segments according to their roles, and evaluated them over more than 1,000 hours of actual broadcast video data.