Evaluating visual quality of digital content

A quality and content technology, applied in the field of data processing, can solve the problems of digital component quality impact, poor quality, image blurring, etc., to avoid the need for repeated evaluation of the same image, and to achieve the effect of efficient image quality

Pending Publication Date: 2022-05-27
GOOGLE LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In some cases, even the individual content assets used to form the Digital Components are of poor quality—such as blurry images, including objectionable content (e.g., sexually explicit content), having incompatible Orientation of regions, etc. - the quality of the resulting digital components may also be negatively affected

Method used

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  • Evaluating visual quality of digital content
  • Evaluating visual quality of digital content
  • Evaluating visual quality of digital content

Examples

Experimental program
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Embodiment Construction

[0022] figure 1 A computing environment 102 is shown in which the quality of one or more content assets 104 forming digital components 106 may be used to regulate the distribution of content. In some examples, content assets 104 may be one or more of images, text, audio, animation, video, interactive content, any other multimedia and / or user interface elements (such as interactive buttons), digital components 106 Can be a combination of two or more of the content assets 104 .

[0023]Computing environment 102 includes a content distribution system 107 (eg, including one or more servers or one or more other data processing devices) from content providers 108 or Content server 110 receives content assets 104 , assembles (eg, combines) at least some of those content assets 104 to form different digital components 106 , and transmits digital components 106 to various client devices 114 in response to external calls 112 . For brevity, the following discussion will refer to conten...

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PUM

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Abstract

Systems, devices, methods, and computer-readable media for assessing visual quality of digital content are disclosed. A method may include identifying content assets that include one or more images, the content assets being combined to create different digital components that are distributed to one or more client devices. The quality of each of the one or more images is evaluated using one or more machine learning models that are trained to evaluate one or more aspects that are considered as an indication of visual quality. An aggregate quality of the content asset is determined based at least in part on an output of the one or more machine learning models, the output indicating a visual quality of each of the one or more images. A graphical user interface of the first computing device is updated to present a visual indication of the aggregated quality of the content asset.

Description

technical field [0001] This specification relates generally to data processing, and more specifically to digital content assessment. Background technique [0002] Computing devices can create digital components and distribute them to various client devices. A digital component may be formed from content assets, such as images, text, etc., that are combined together to form the digital component. In some cases, even the individual content assets used to form the digital components are of poor quality - such as blurred images, including objectionable content (eg, sexually explicit content), having Orientation of areas, etc. - the quality of the resulting digital components may also be negatively affected. SUMMARY OF THE INVENTION [0003] In general, one innovative aspect of the subject matter described in this specification may be embodied in a method comprising the operations of identifying, by one or more processors, a content asset comprising one or more images, the C...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/55G06N3/04G06N3/08G06N20/20G06Q30/02
CPCG06F16/55G06N3/08G06N20/20G06Q30/0244G06N3/045G06Q50/10
Inventor C.徐李璐莹杨峰柯均洁罗曦杨冯浩陈昭宏康雯婧Z.夏陈舜全田怡聪李霞柯瀚
Owner GOOGLE LLC
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