Self-Calibrating Camera Model Using Night Sky Star Patterns
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Solution Overview
Problem
Existing technologies face challenges in accurately defining camera models for computing device cameras, especially for undefined or poorly characterized devices, due to variations in focal plane and lens properties, and the inconvenience and expense of traditional characterization methods.
Innovation Solution
A computing device with a camera can define and iteratively update a camera model by using location data from objects in night sky images and corresponding cataloged stars, employing algorithms like focus stacking and pattern matching to refine the model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional lab-based camera model characterization is performed, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The computing device performs self-characterization by capturing images of the night sky and automatically computing its own camera model parameters through pattern matching algorithms, eliminating the need for external lab equipment and procedures
Solution Approach 2:
The system uses a catalog of known star positions as a reference model to compute camera parameters, creating a virtual reference system that replaces physical calibration targets and lab infrastructure
2Measurement precision
If traditional lab-based camera model characterization is performed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The computing device autonomously performs characterization using only its camera and processor, eliminating the need to transport devices to laboratories and perform manual measurements, thereby dramatically reducing characterization time
Solution Approach 2:
The system uses pre-existing astronomical catalogs of star positions as reference data, eliminating the need to create physical calibration targets or perform preliminary setup procedures in a lab environment
3Measurement precision
If traditional lab-based camera model characterization is performed, then measurement precision is improved, but loss of substance increases
Solution Approach 1:
The system performs iterative refinement of camera parameters, computing models with varying levels of precision and selecting appropriate accuracy levels based on application requirements, avoiding unnecessary computational expenditure
Data Source
AI summary
According to one example embodiment, a computing device can include a camera, one or more processors, and one or more computer-readable media that store instructions that, when executed by the one or more processors, cause the computing device to perform operations. The operations can include defining a camera model of the camera based at least in part on location data associated respectively with an object in an image of a night sky and a cataloged star that corresponds to the object. The operations can further include performing an iterative process to iteratively update the camera model. For at least one iteration of the iterative process the operations can further include updating the camera model based at least in part on additional location data associated respectively with an additional object in an additional image of the night sky and an additional cataloged star that corresponds to the additional object.