Abstract
As a robust media representation technique, video hashing is frequently used in near-duplicate detection, video authentication, and antipiracy search. Distortions to a video may include spatial modifications to each frame, temporal de-synchronization, and joint spatio-temporal attacks. To address the increasingly difficult case of finding videos under spatio-temporal modifications, we propose a new framework called two-stage video hashing. First, an efficient automatic synchronization is achieved using dynamic time warping (DTW) and a complementary video comparison measure is developed based on flow hashing (FH), which is extracted from the synchronized videos. Next, a fusion mechanism called distance boosting is proposed to fuse the information extracted by DTW and FH in a future–proof manner in the sense whenever model retraining is needed, the existing hash vectors do not need to be regenerated. Experiments on real video collections show that such a hash extraction and fusion method enables unprecedented robustness under both spatial and temporal attacks.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Information Forensics and Security
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
