Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
VideoQ: an automated content based video search system using visual cues
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Ordinal Measures for Image Correspondence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Extraction and a Database Strategy for Video Fingerprinting
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Multimedia Systems - Special section on video libraries
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Towards effective indexing for very large video sequence database
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A Clustering Technique for Video Copy Detection
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Continuous Content-Based Copy Detection over Streaming Videos
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Spatio–Temporal Transform Based Video Hashing
IEEE Transactions on Multimedia
Content-Based Copy Retrieval Using Distortion-Based Probabilistic Similarity Search
IEEE Transactions on Multimedia
Forensic analysis of nonlinear collusion attacks for multimedia fingerprinting
IEEE Transactions on Image Processing
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
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video copy detection is intended for verifying whether a video sequence is copied from another or not. Such techniques can be used for protecting the copyright. A content-based video detection system extracts signature of the video from its visual constituents. Signature of the test sequence is matched against the same of the sequences in the database. Deciding whether two sequences are similar enough even with the presence of distortion is a big challenge. In this work, we have focused on sequence matching. We have proposed a hypothesis test based scheme for comparing the similarity of two sequences. Experiments have been carried out to verify the capability of the concept and result seems satisfactory.