Video fingerprinting based on graph model

Abstract

A robust video fingerprinting based on graph model is proposed in this paper, where two graph models are constructed for key frames selection and foreground extraction, respectively. First, the video is represented as a complete undirected graph and a binary tree is formed using normalized cut algorithm to select key frames. Then, the pixels of each key frame are modeled as a Markov Random Field and another graph model is formed to extract foreground by graph cut. Finally, the fourth-order cumulant of foreground is computed to generate video fingerprints. Experimental results show that the proposed algorithm has good robustness and discrimination.

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