- Number
- 20240362896
- Published
- 2024-10-31
- Filed
- 2024-04-11
- Assignee
- Disney Enterprises, Inc.
- Inventors
- Xue; Yuanyi et al.
- CPC
- G06N20/00; G06T7/0002; G06V10/26; G06V10/774; H04N21/23418; H04N21/252; H04N21/44008; H04N21/4667; H04N21/4756
- Verdict
- Set aside media QC tool, business
- Source
- Google Patents · FreePatentsOnline
Abstract
In some embodiments, a method sends information for a sample of content, a first question, and a second question for output on an interface. The first question receives, from a subject, a first response for a sample level rating for an artifact that is perceived to be visible in the sample and the second question receives, from the subject, a second response for regions in the sample that are perceived to contain the artifact. The method receives the first response for the sample level rating and the second response for regions that are perceived to contain the artifact. First responses are combined from multiple subjects to generate an opinion score for the sample and second responses are combined to generate region scores for regions. The method generates training data from the opinion score and the region scores to train a process to perform an action based on the artifacts.
Background
BACKGROUND
Artifacts in digital video may be distortions that appear in the video. Different types of artifacts may occur. For example, one artifact is banding, which may be where a continuous change of luminance and chrominance becomes a sudden drop in values creating visible bands that should not be present in the video. The banding artifact may occur when the available bit depth for presenting the luminance or chrominance information is limited. That is, having 8 bits to represent the luminance and chrominance information may result in more visible bands compared to having more bit depth, such as 10 or 12 bits, to represent the luminance and chrominance information. Other artifacts may also result in video for different reasons.
A video delivery system may want to mitigate the occurrence of the artifacts that may occur in a video. However, it may be challenging to identify and measure the artifacts, and then later mitigate the artifacts.
Claims
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 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 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 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. ||
16. A non-transitory computer-readable storage medium having stored thereon computer executable instructions, which when executed by a computing device, cause the computing device to be operable for: 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 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 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 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. ||
17. A method comprising: outputting a sample of content, a first question, and a second question on an interface; receiving, from a subject, a first response to the first question for a sample level rating for an artifact that is perceived to be visible in the sample that is output on the interface; receiving, from the subject, a second response to the second question for one or more regions in a plurality of regions in the sample that are perceived to contain the artifact; and sending the first response and the second response to a server system, wherein the first responses from multiple subjects are combined to generate an opinion score for the sample from the first responses and second responses from the multiple subjects are combined to generate region scores for regions in the plurality of regions, and training data is generated 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.