Virtual Face Representation for Automatic Image Correction
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Solution Overview
Problem
Conventional image editing techniques are inadequate for correcting blurring or obscuring of faces in photographs, requiring significant manual editing and failing to improve user experience in image processing on computing devices.
Innovation Solution
The system generates a virtual representation of a user's face using manifold learning to capture variations in lighting, expressions, and angles, allowing for automatic adjustment and enhancement of facial images, including opening closed eyes, removing blurring, and modifying facial expressions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional image editing techniques are used to correct blurring or obscuring of faces, then some basic editing can be performed, but the editing process requires significant manual effort and time
Solution Approach 1:
The system enables automatic face correction by having the computing device perform the editing operations autonomously. The processor automatically detects blurred or obscured faces in images and applies correction algorithms without requiring manual user intervention, thus resolving the contradiction between achieving high correction quality and minimizing manual editing time
Solution Approach 2:
The patent replaces manual mechanical editing operations with automated computational processing. Instead of users manually adjusting pixels and parameters, the system uses processors to automatically analyze and correct face blurring and obscuring, substituting human manual effort with automated image processing algorithms
2Reliability
If conventional image editing techniques are used, then basic adjustments can be made, but the techniques are insufficient for effectively correcting face blurring or obscuring
Solution Approach 1:
The system changes the parameters of image processing by applying specific correction algorithms tailored for face blurring and obscuring. The processor adjusts multiple image parameters simultaneously (sharpness, clarity, detail preservation) using advanced algorithms that go beyond conventional single-parameter adjustments, thereby improving correction effectiveness while managing system complexity through specialized processing
3Manufacturing precision
If manual image editing is performed to correct face issues, then some corrections can be achieved, but the process is inconvenient and decreases user experience
Solution Approach 1:
The system performs image correction automatically without requiring user interaction. The computing device self-services by detecting face issues and applying corrections autonomously, eliminating the need for users to manually edit images and significantly improving ease of operation while maintaining high correction quality
Data Source
AI summary
A computing device can acquire a set of images, each image including at least a portion of a user's face. The images can be acquired using one or more cameras and/or from an image library/database associated with the user. Based on the images including the user's face (or portions thereof), a virtual representation for the user's face can be generated. The device can subsequently receive or identify an image including a facial representation (e.g., face or portion thereof) to be adjusted. The device can analyze the image including the facial representation and determine that the facial representation sufficiently matches the virtual representation. Using the virtual representation, (at least a portion of) the face can be adjusted. For example, one or more variations or details associated with the user's face, which are provided via the virtual representation, can be used to replace, improve, or otherwise modify the face in the image.