Context-Aware Camera FOV Adjustment for Clear User and Object Images
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Solution Overview
Problem
Existing electronic devices struggle to capture clear images of both users and objects in challenging environmental conditions, such as sun glare or cluttered backgrounds, requiring significant user effort or leading to unsatisfactory results.
Innovation Solution
The system captures context data using sensors and manual inputs to identify objects in the field of view, providing instructions or automatically adjusting the camera to improve image capture, including focus, zoom, and positioning suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If users manually adjust camera settings to capture both user and object clearly, then image quality can be improved, but user time and effort increase significantly
Solution Approach 1:
The camera system automatically performs object identification, scene analysis, and parameter adjustment without requiring manual user intervention. The processor autonomously analyzes captured images, identifies objects using context data, and adjusts camera settings to optimize image quality, enabling the system to serve itself rather than requiring continuous user control.
Solution Approach 2:
The system pre-loads context data about various objects and scenes into the database before actual image capture occurs. When an object is captured, the system quickly compares it against pre-stored context data to identify the object and determine optimal camera parameters, eliminating the need for real-time manual adjustment and significantly reducing user time investment.
2Manufacturing precision
If users spend more time adjusting camera settings and repositioning, then image quality improves, but the efficiency of capturing images decreases
Solution Approach 1:
The system continuously monitors captured images, compares them against context data in the database, and provides real-time feedback about object identification results. Based on this feedback, the processor automatically adjusts camera parameters and guides users on optimal positioning, creating a closed-loop system that rapidly converges on high-quality captures without requiring multiple manual trial-and-error attempts.
Solution Approach 2:
The patent replaces manual mechanical adjustment of camera settings and physical repositioning with automated electronic control. The processor electronically adjusts focus, exposure, and other camera parameters based on automated object recognition, substituting the mechanical user-adjustment process with an automated computational system that operates much faster and more efficiently.
3Productivity
If the camera automatically adjusts settings without user input, then image capture efficiency improves, but image quality may deteriorate due to lack of user control
Solution Approach 1:
The camera system autonomously performs the complete image capture process including object identification, scene analysis, parameter optimization, and capture execution without requiring user control inputs. The system serves itself by automatically managing all aspects of the imaging process while maintaining high quality through sophisticated automated analysis and decision-making algorithms.
Solution Approach 2:
The processor dynamically changes multiple camera parameters simultaneously based on automated object recognition and scene analysis. By computationally optimizing parameters such as focus distance, exposure time, aperture settings, and digital zoom level based on real-time analysis of captured images and comparison with context data, the system achieves high image quality through automated parameter adjustment rather than manual user control.
Data Source
AI summary
An electronic device for capturing images is provided that can include a camera and one or more processors. The electronic device can also include a memory storing program instructions accessible by the one or more processors. Responsive to execution of the program instructions, the one or more processors are configured to obtain context data for a scene in a field of view (FOV) of the camera of the electronic device, identify an object in the FOV based on the context data; and provide instructions related to the FOV or operate the camera to adjust the FOV based on the object identified.