  In this work, we propose a joint audio-video fingerprint Automatic Content
Recognition (ACR) technology for media retrieval. The problem is focused on how
to balance the query accuracy and the size of fingerprint, and how to allocate
the bits of the fingerprint to video frames and audio frames to achieve the
best query accuracy. By constructing a novel concept called Coverage, which is
highly correlated to the query accuracy, we are able to form a rate-coverage
model to translate the original problem into an optimization problem that can
be resolved by dynamic programming. To the best of our knowledge, this is the
first work that uses joint audio-video fingerprint ACR technology for media
retrieval with a theoretical problem formulation. Experimental results indicate
that compared to reference algorithms, the proposed method has up to 25% query
accuracy improvement while using 60% overall bit-rates, and 25% bit-rate
reduction while achieving 85% accuracy, and it significantly outperforms the
solution with single audio or video source fingerprint.
