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A Clustering Technique for Video Copy Detection

2007; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-540-72847-4_58

1611-3349

Nicolás Guil, José María González-Linares, Julián Ramos Cózar, Emilio L. Zapata,

Multimedia Communication and Technology

In this work, a new method for detecting copies of a query video in a videos database is proposed. It includes a new clustering technique that groups frames with similar visual content, maintaining their temporal order. Applying this technique, a keyframe is extracted for each cluster of the query video. Keyframe choice is carried out by selecting the frame in the cluster with maximum similarity to the rest of frames in the cluster. Then, keyframes are compared to target videos frames in order to extract similarity regions in the target video. Relaxed temporal constraints are subsequently applied to the calculated regions in order to identify the copy sequence. The reliability and performance of the method has been tested by using several videos from the MPEG-7 Content Set, encoded with different frame sizes, bit rates and frame rates. Results show that our method obtains a significant improvement with respect to previous approaches in both achieved precision and computation time.