Automatic Camera Ground Plane Calibration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing surveillance camera systems require manual configuration of ground planes, which is complex, costly, and prone to errors, and must be repeated for each camera and whenever the camera's field of view changes.
Innovation Solution
The system automatically generates ground planes using machine learning algorithms trained on captured images, with an ambiguity detection module that updates the planes based on object tracking and classification information to address errors and changes in the scene or camera view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual configuration of ground planes is used, then ground plane calibration can be achieved, but the process is complex, costly, and error-prone
Solution Approach 1:
The system performs self-calibration by automatically detecting the ground plane from image data without requiring manual operator intervention. The calibration module processes images to identify the ground plane region and computes its parameters autonomously, eliminating the need for operators to manually draw regions or input measurements.
Solution Approach 2:
The patent replaces manual mechanical calibration operations with automated computational processing. Instead of operators physically measuring reference objects and inputting data, the system uses image processing algorithms to automatically detect and compute ground plane parameters from captured images.
2Measurement precision
If manual ground plane configuration is performed for each camera, then accurate ground plane definition is achieved, but the process is time-consuming and must be repeated for every camera
Solution Approach 1:
Each camera performs self-calibration by automatically processing its own image data to define its ground plane. The calibration module operates autonomously on each camera's images, eliminating the need for operators to manually calibrate each camera individually.
Solution Approach 2:
The system performs ground plane calibration as an initial setup step that is automatically executed during system initialization or camera installation. By automating this preliminary action, the system eliminates the need for repeated manual calibration when cameras are added or repositioned.
3Measurement precision
If manual calibration is repeated whenever field of view changes, then ground plane accuracy is maintained, but operational efficiency decreases
Solution Approach 1:
The system continuously monitors changes in camera field of view and automatically triggers ground plane recalibration only when necessary. The calibration module detects FOV changes and performs updates selectively, maintaining accuracy while avoiding unnecessary recalibrations that would reduce operational efficiency.
Solution Approach 2:
The ground plane calibration is made dynamic and adaptive, automatically adjusting to camera repositioning or FOV changes. The system transitions from static manual calibration to dynamic automatic recalibration that responds to actual operational conditions, maintaining accuracy without requiring constant manual intervention.
4Measurement precision
If reference objects are used for calibration, then ground plane parameters can be determined, but the process is tedious and error-prone
Solution Approach 1:
The system eliminates the need for operators to select and measure reference objects by implementing automatic ground plane detection. The calibration module processes image data to identify the ground plane region and compute its parameters autonomously, removing the tedious manual steps of reference object selection and measurement.
Solution Approach 2:
The patent replaces manual reference object measurement with automated image processing. Instead of operators identifying and measuring physical reference objects in the scene, the system uses computational algorithms to detect the ground plane directly from image pixel data and compute calibration parameters.
Data Source
AI summary
A surveillance camera system and method is disclosed. The system includes one or more surveillance cameras that capture images of scenes, and one or more calibration systems that automatically generate ground planes from the captured images from the surveillance cameras. Foreground objects in the scenes are then analyzed against the ground planes to determine whether the ground planes may require updating and/or recalculation.