US 12,469,262 B2
Subjective quality assessment tool for image/video artifacts
Yuanyi Xue, Alameda, CA (US); Scott Labrozzi, Cary, NC (US); Wenhao Zhang, Beijing (CN); Christopher Richard Schroers, Uster (CH); Roberto Gerson De Albuquerque Azevedo, Zurich (CH); Xuchang Huangfu, Beijing (CN); Lemei Huang, Beijing (CN); and Yang Zhang, Dübendorf (CH)
Assigned to Disney Enterprises, Inc., Burbank, CA (US); and Beijing YoJaJa Software Technology Development Co., Ltd., Beijing (CN)
Filed by Disney Enterprises, Inc., Burbank, CA (US); and Beijing YoJaJa Software Technology Development Co., Ltd., Beijing (CN)
Filed on Apr. 11, 2024, as Appl. No. 18/633,170.
Claims priority of provisional application 63/498,642, filed on Apr. 27, 2023.
Prior Publication US 2024/0362896 A1, Oct. 31, 2024
Int. Cl. G06V 10/774 (2022.01); G06T 7/00 (2017.01); G06V 10/26 (2022.01)
CPC G06V 10/774 (2022.01) [G06T 7/0002 (2013.01); G06V 10/26 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30168 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
sending information for a sample of content, a first question, and a second question for output on an interface, wherein the first question is configured to receive, from a subject, a first response for a sample level rating for an artifact that is perceived to be visible in the sample of content and the second question is configured to receive, from the subject, a second response for one or more regions in a plurality of regions in the sample of content that are perceived to contain the artifact;
receiving the first response for the sample level rating and the second response for one or more regions that are perceived to contain the artifact;
combining first responses for the first question from multiple subjects to generate an opinion score for the sample of content and combining second responses for the second question from the multiple subjects to generate region scores for regions in the plurality of regions; and
generating training data from the opinion score and the region scores to train a process to perform an action based on the artifacts in one or more regions in the sample of content, wherein generating training data comprises:
determining a cropped patch of a portion of the sample of content;
determining regions that are included in the cropped patch; and
determining a patch score based on region scores for the regions that are included in the cropped patch.