Dynamic Multi-Camera Calibration Using Feature-Rich Image Frames
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Solution Overview
Problem
Multi-camera platforms face challenges in maintaining accurate camera calibration over time due to changes in ambient temperature, orientation, and physical deformations, leading to errors in computational imaging tasks, especially in consumer devices where field calibration is tedious and difficult to replicate.
Innovation Solution
A dynamic calibration method that uses multiple captured images to refine camera calibration parameters, selecting feature-rich images based on optimality criteria to improve accuracy and reduce computation time, with low-frequency parameters shared across images and high-frequency parameters treated uniquely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If factory calibration is performed to ensure accurate camera parameters, then manufacturing precision is improved, but the calibration cannot adapt to changes over time due to temperature, orientation, and physical deformations
Solution Approach 1:
The patent implements dynamic calibration by capturing multiple image frames over time and updating calibration parameters continuously. Instead of relying on static factory calibration, the system adapts calibration parameters to changing environmental conditions (temperature, orientation, physical deformations) by processing sequences of images and computing updated intrinsic and extrinsic parameters that reflect current platform state.
2Adaptability or versatility
If dynamic calibration uses captured images of natural scenes to refine calibration parameters, then adaptability is improved, but capturing scenes with suitable feature count and distribution becomes difficult
Solution Approach 1:
The system performs self-calibration by using naturally captured images from the environment rather than requiring external calibration targets. The calibration process serves itself by extracting feature points from ordinary scene images that the camera captures during normal operation, eliminating the need for specialized calibration equipment or controlled environments.
Solution Approach 2:
The patent changes the approach from requiring specific calibration targets to using variable natural scenes by implementing robust feature detection and selection criteria. The system evaluates multiple captured images and selects those with optimal feature distributions, using parameter-based scoring to identify images suitable for calibration even in unpredictable consumer environments.
3Measurement precision
If multiple image frames are used for dynamic calibration, then calibration accuracy is improved, but computation time increases
Solution Approach 1:
The patent applies partial action by selecting a subset of captured images for calibration rather than processing all available frames. The system scores and evaluates multiple images, then chooses only those meeting specific quality criteria (feature count, distribution, geometric diversity) for the calibration process, reducing computation while maintaining or improving accuracy.
Solution Approach 2:
The system performs preliminary evaluation and scoring of captured images before committing to the full calibration process. By pre-assessing image quality metrics (feature point distribution, scene geometry, calibration suitability) and selecting optimal frames in advance, the system prepares the best input data for calibration, reducing iterative computation time while ensuring high accuracy results.
Data Source
AI summary
System, apparatus, method, and computer readable media for on-the-fly dynamic calibration of multi-camera platforms using images of multiple different scenes. Image frame sets previously captured by the platform are scored as potential candidates from which new calibration parameters may be computed. The candidate frames are ranked according to their score and iteratively added to the calibration frame set according to an objective function. The selected frame set may be selected from the candidates based on a reference frame, which may be a most recently captured frame, for example. A device platform including a CM and comporting with the exemplary architecture may enhance multi-camera functionality in the field by keeping calibration parameters current. Various computer vision algorithms may then rely upon these parameters, for example.