Retrieval of News Video Using Video Sequence Matching
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
Fast similarity search and clustering of video sequences on the world-wide-web
IEEE Transactions on Multimedia
An integrated scheme for automated video abstraction based on unsupervised cluster-validity analysis
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Efficient video similarity measurement with video signature
IEEE Transactions on Circuits and Systems for Video Technology
Spatiotemporal sequence matching for efficient video copy detection
IEEE Transactions on Circuits and Systems for Video Technology
A new key frame representation for video segment retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Video copy detection: sequence matching using hypothesis test
AST/UCMA/ISA/ACN'10 Proceedings of the 2010 international conference on Advances in computer science and information technology
Computational intelligence in multimedia processing
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
Effective web video clustering using playlist information
Proceedings of the 27th Annual ACM Symposium on Applied Computing
A new video watermarking algorithm based on shot segmentation and block classification
Multimedia Tools and Applications
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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.