Camera Calibration via Object Tracking and Distortion Correction
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Solution Overview
Problem
The calibration of cameras for accurate tracking of organic and non-organic objects is labor-intensive and costly due to lens distortions, requiring manual calibration steps and alignment with calibrated targets, which hinders efficient path length measurement and spatial view generation.
Innovation Solution
A method for automatically calibrating cameras by receiving images, identifying and tracking objects, inferring perspective from object size changes, and creating a metrical map using ground pixel locations, which corrects for distortion and perspective effects, employing segmentation models and statistical inference to build accurate 2D maps of spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration with calibrated targets is used, then measurement precision is improved, but loss of time and productivity deteriorate due to labor-intensive calibration steps
Solution Approach 1:
The system performs self-calibration by automatically detecting objects in the scene and using their known dimensions to infer camera parameters and distortion characteristics, eliminating the need for manual calibration with calibrated targets
Solution Approach 2:
The patent replaces the mechanical manual alignment and calibration process with an automated computer vision system that uses object detection, tracking, and statistical inference to determine camera parameters and correct distortions
2Manufacturing precision
If manual alignment with calibrated targets is performed, then manufacturing precision is improved, but device complexity increases due to additional calibration equipment and steps
Solution Approach 1:
The patent extracts the calibration function from separate manual procedures and calibrated target equipment, integrating it into the normal object detection and tracking workflow using everyday objects in the scene
Solution Approach 2:
The system uses ordinary objects with known dimensions (such as people, vehicles, or standard equipment) for calibration purposes, making the calibration process universal and eliminating the need for specialized calibrated targets
3Measurement precision
If traditional calibration methods are used, then measurement accuracy is improved, but ease of operation deteriorates due to complex calibration procedures
Solution Approach 1:
The calibration process occurs automatically without user intervention - the system detects objects, tracks their movement, and computes calibration parameters on its own
Solution Approach 2:
The system performs calibration actions in advance by continuously monitoring object positions and sizes, building up statistical data that is used to correct measurements before they are reported to the user
Data Source
AI summary
Provided are a method and system for calibrating a camera to correct for perspective and lens distortion. The video camera provides images to a computer, which identifies objects and tracks their movement during a calibration period. Changes in size of the tracked objects are used to infer perspective and distortion in the video camera. A map of the room may be created noting locations of objects and flooring surfaces. Movement of objects along the floor may be measured more accurately using the calibrated camera images.