Vehicle Camera Alignment Calibration via Global Optimization
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Solution Overview
Problem
Existing methods for calibrating cameras on vehicles, particularly those pointing sideways, face challenges due to small overlap regions and errors in relative calibration, leading to inconsistent and potentially worsening calibration results when averaging delta poses.
Innovation Solution
A method that involves acquiring camera images, ascertaining overlap regions, setting up a common optimization function to describe camera alignments, and solving this function to determine camera alignments simultaneously in a common coordinate system, eliminating the need for heuristic harmonization and averaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If relative calibration is performed by averaging multiple delta poses from overlap regions, then calibration can be achieved for side cameras, but calibration accuracy deteriorates due to error distribution and small overlap regions
Solution Approach 1:
The patent merges multiple individual calibration problems into a single unified optimization problem. Instead of separately calibrating each camera pair and then averaging results, all cameras are calibrated simultaneously by combining their overlap region constraints into one global optimization function, which directly minimizes the sum of squared errors across all cameras and overlap regions.
Solution Approach 2:
The patent transitions from pairwise calibration (2D problem between two cameras) to multi-camera simultaneous calibration (n-dimensional problem involving all cameras). This dimensional expansion allows the system to resolve ambiguities that cannot be solved in lower dimensions by considering all camera constraints together.
2Device complexity
If heuristic averaging is used to harmonize individual delta poses, then an over-determined system can be resolved, but systematic errors are distributed rather than eliminated
Solution Approach 1:
The patent replaces the mechanical/heuristic averaging approach with a mathematical optimization approach. Instead of simply averaging delta poses, the system formulates a global optimization function that mathematically minimizes calibration errors across all cameras simultaneously, substituting heuristic methods with rigorous mathematical optimization.
Solution Approach 2:
The optimization function continuously evaluates calibration accuracy by computing the sum of squared errors between projected and actual feature point positions. This feedback mechanism guides the iterative optimization process to converge toward the optimal calibration parameters that minimize overall system error.
3Quantity of substance
If multiple overlap regions are used for calibration, then more relative poses can be obtained, but the over-determined system requires heuristic harmonization that may worsen calibration
Solution Approach 1:
The patent segments the calibration problem into individual camera contribution terms within a unified optimization framework. Each camera's calibration parameters are optimized independently through their respective overlap region constraints, but these segmented problems are solved simultaneously within the global optimization function, eliminating the need for post-processing harmonization.
Data Source
AI summary
A method for calibrating a multiplicity of cameras on a vehicle in a common coordinate system. The method includes: a) acquiring camera images using each camera of the multiplicity of cameras, b) ascertaining overlap regions of camera images acquired in step a), c) setting up a common optimization function, which describes the alignments of each camera of the multiplicity of cameras as a target variable of the optimization, based on the overlap regions, d) solving the common optimization function set up in step c) to ascertain the alignments of each camera.