A distance measure for video sequence similarity matching

Contrary to current approaches which generally treat the video data as a random collection of static images, content-based video retrieval requires methods for video sequence-to-sequence matching incorporating the temporal order inherent in video data. We formulate the problem of video sequence-to-sequence matching as a pattern matching problem. New string edit operations required for the special characteristics of video sequences and the unique features of the vstring representation are introduced. Based on the edit operations, the vstring edit distance is proposed as a new similarity measure for video sequence matching.