US 12,002,261 B2
Iterative media object compression algorithm optimization using decoupled calibration of perceptual quality algorithms
Luitpold Staudigl, Bonn (DE); Thomas Sydney Austin Wallis, Teubingen (DE); Mike Mueller, Tuebingen (DE); Muhammad Bilal Javed, Berlin (DE); and Pablo Barbachano, Berlin (DE)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on Dec. 9, 2022, as Appl. No. 18/064,192.
Application 18/064,192 is a continuation of application No. 16/875,884, filed on May 15, 2020, granted, now 11,527,019.
Prior Publication US 2023/0103873 A1, Apr. 6, 2023
Int. Cl. G06V 10/82 (2022.01); G06F 18/214 (2023.01); G06F 18/25 (2023.01); G06N 3/082 (2023.01); G06N 3/086 (2023.01); G06N 20/20 (2019.01); G06T 3/4046 (2024.01); G06T 7/00 (2017.01); G06T 9/00 (2006.01); G06V 10/774 (2022.01); G06V 10/778 (2022.01); G06V 10/80 (2022.01)
CPC G06V 10/82 (2022.01) [G06F 18/214 (2023.01); G06F 18/251 (2023.01); G06N 3/082 (2013.01); G06N 3/086 (2013.01); G06N 20/20 (2019.01); G06T 3/4046 (2013.01); G06T 7/0002 (2013.01); G06T 9/002 (2013.01); G06V 10/774 (2022.01); G06V 10/7784 (2022.01); G06V 10/7788 (2022.01); G06V 10/803 (2022.01); G06T 2207/30168 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
obtaining, via one or more programmatic interfaces of a network-accessible service of a cloud computing environment, an indication of a factor for classifying a plurality of media objects into importance categories, including a first importance category and a second importance category;
identifying (a) a first set of class-specific tuned parameter values to be used to compress media objects of the first importance category, and (b) a second set of class-specific tuned parameter values to be used to compress media objects of the second importance category, wherein:
the first set of class-specific tuned parameter values have been tuned using example media objects classified as the first importance category, and
the second set of class-specific tuned parameter values have been tuned using example media objects classified as the second importance category;
compressing, prior to a display of a first media object, the first media object using the first set of class-specific tuned parameter values, wherein the first media object is classified, using the factor, as belonging to the first importance category; and
compressing, prior to a display of a second media object, the second media object using the second set of class-specific tuned parameter values, wherein the second media object is classified, using the factor, as belonging to the second importance category.