Apple inc. (20240112303). Context-Based Selection of Perspective Correction Operations simplified abstract
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 20240112303 titled 'Context-Based Selection of Perspective Correction Operations
Simplified Explanation
The method described in the abstract involves obtaining image data associated with a physical environment, obtaining contextual information related to the user, application, and environment, selecting perspective correction operations based on the contextual information, generating corrected image data, and presenting the corrected image data.
- Obtaining image data associated with a physical environment
- Obtaining contextual information including user information, application information, and environment information
- 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, gaming, navigation, and interior design.
Problems Solved
This technology solves the problem of distorted or skewed images in a physical environment, providing a more accurate representation for users.
Benefits
The benefits of this technology include improved user experience, enhanced visualization, accurate image representation, and better context awareness.
Potential Commercial Applications
One potential commercial application of this technology could be in the development of augmented reality applications for real estate, where accurate representation of properties is crucial for potential buyers.
Possible Prior Art
One possible prior art for this technology could be image processing techniques used in computer vision applications to correct distortions in images.
Unanswered Questions
How does this technology handle real-time image correction?
This article does not delve into the specifics of real-time image correction capabilities of the technology. Real-time processing requirements and latency issues could be crucial factors in certain applications.
What are the computational requirements for performing perspective correction operations?
The article does not address the computational resources needed to execute the perspective correction operations. Understanding the computational overhead can be essential for optimizing the performance of the system.
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.
