Synchronized digital video subsampling to achieve temporal resolution independence

In this paper, we present a selective video sub-sampling algorithm to achieve temporal resolution independence in applications with hard requirements on frame sequentiality, especially targeted to video identification systems based on fingerprint strings. The algorithm extracts video entropy, and based on the resulting series, a set of intervals and frames for each interval are selected. The same exact intervals and frames can be repeatedly extracted for any other variation of the original content, which is especially desirable when variations have undergone dramatic quality and frame rate reduction in their distribution. Different from basic subsampling techniques, the proposed method is not just able to get a frame set of equal length for different frame rate variations, but the generated set includes more frames when events are going on in the video, while less frames are chosen when the video content remains steady. This fact provides a significant improve of performance in terms of recall and precision values in video identification applications.