US 12,192,591 B2
Training an encrypted video stream network scoring system with non-reference video scores
Michael Colligan, Sunnyvale, CA (US); and Jeremy Bennington, Greenwood, IN (US)
Assigned to Spirent Communications, Inc., San Jose, CA (US)
Filed by Spirent Communications, Inc., San Jose, CA (US)
Filed on Aug. 1, 2022, as Appl. No. 17/878,813.
Application 17/878,813 is a division of application No. 16/842,676, filed on Apr. 7, 2020, granted, now 11,405,695.
Claims priority of provisional application 62/831,114, filed on Apr. 8, 2019.
Prior Publication US 2022/0368995 A1, Nov. 17, 2022
Int. Cl. H04N 21/647 (2011.01); H04N 21/234 (2011.01)
CPC H04N 21/64738 (2013.01) [H04N 21/23418 (2013.01); H04N 21/64784 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A non-transitory computer readable media impressed with program instructions that, when executed on hardware, cause the hardware to perform a method of monitoring video quality of delivered video streams on a live network, the method including:
measuring network conditions including actual bit rate during delivery of numerous video streams at a plurality of locations on the live network, correlated with data identifying a video source per video stream;
applying a trained classifier to the measured network conditions and the correlated data to assign video quality scores without dependence on rendering images from the video streams;
aggregating the assigned video quality scores based on one or more parameters of the measured network conditions and the identifying data; and
storing at least the aggregated video quality scores.