18371872. Context-Based Selection of Perspective Correction Operations simplified abstract (Apple Inc.)
Contents
- 1 Context-Based Selection of Perspective Correction Operations
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Context-Based Selection of Perspective Correction Operations - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
Context-Based Selection of Perspective Correction Operations
Organization Name
Inventor(s)
Vincent Chapdelaine-couture of Carignan (CA)
Emmanuel Piuze-phaneuf of Los Gatos CA (US)
Julien Monat Rodier of San Francisco CA (US)
Hermannus J. Damveld of Santa Clara CA (US)
Xiaojin Shi of Cupertino CA (US)
Sebastian Gaweda of Cupertino CA (US)
Context-Based Selection of Perspective Correction Operations - A simplified explanation of the abstract
This abstract first appeared for US patent application 18371872 titled 'Context-Based Selection of Perspective Correction Operations
Simplified Explanation
The abstract describes a method that involves obtaining image data associated with a physical environment, obtaining contextual information related to user, application, and environment states, selecting perspective correction operations based on this information, generating corrected image data, and presenting it.
- Obtaining image data related to a physical environment
- Obtaining contextual information such as user state, application being used, and physical environment state
- Selecting perspective correction operations based on contextual information
- Generating corrected image data by applying perspective correction operations
- Presenting the corrected image data
Potential Applications
This technology could be applied in various fields such as augmented reality, virtual reality, image processing, and computer vision.
Problems Solved
This technology addresses the issue of correcting perspective distortion in images to provide a more accurate representation of the physical environment.
Benefits
The benefits of this technology include improved visual quality, enhanced user experience, and more accurate spatial perception in applications.
Potential Commercial Applications
Potential commercial applications of this technology include AR/VR systems, photography software, mapping and navigation tools, and surveillance systems.
Possible Prior Art
One possible prior art could be existing image processing techniques used for perspective correction in photography and computer vision applications.
What are the specific types of perspective correction operations used in this method?
The specific types of perspective correction operations used in this method are not explicitly mentioned in the abstract. Further details on the exact operations involved would provide a clearer understanding of the technical implementation.
How does the method determine the appropriate level of correction needed for the image data?
The abstract does not specify how the method determines the appropriate level of correction needed for the image data. Understanding the criteria or algorithms used for this determination would be crucial for assessing the accuracy and effectiveness of the perspective correction process.
Original Abstract Submitted
In some implementations, a method includes: obtaining image data associated with a physical environment; obtaining first contextual information including at least one of first user information associated with a current state of a user of the computing system, first application information associated with a first application being executed by the computing system, and first environment information associated with a current state of the physical environment; selecting a first set of perspective correction operations based at least in part on the first contextual information; generating first corrected image data by performing the first set of perspective correction operations on the image data; and causing presentation of the first corrected image data.
