Robust efficient video fingerprinting
2009
We have developed a video fingerprinting system with robustness and efficiency as the primary and secondary design
criteria. In extensive testing, the system has shown robustness to cropping, letter-boxing, sub-titling, blur, drastic
compression, frame rate changes, size changes and color changes, as well as to the geometric distortions often associated
with camcorder capture in cinema settings. Efficiency is afforded by a novel two-stage detection process in which a fast
matching process first computes a number of likely candidates, which are then passed to a second slower process that
computes the overall best match with minimal false alarm probability. One key component of the algorithm is a
maximally stable volume computation - a three-dimensional generalization of maximally stable extremal regions - that
provides a content-centric coordinate system for subsequent hash function computation, independent of any affine
transformation or extensive cropping. Other key features include an efficient bin-based polling strategy for initial
candidate selection, and a final SIFT feature-based computation for final verification. We describe the algorithm and its
performance, and then discuss additional modifications that can provide further improvement to efficiency and accuracy.
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