Camera Calibration via Optically Encoded Moving Object Indicators
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Solution Overview
Problem
Existing camera surveillance networks face challenges in precise calibration of multiple cameras, often relying on rough GPS estimates and manual adjustments due to lack of synchronization, leading to inaccurate geo-positional matching and tedious calibration processes.
Innovation Solution
A method involving an optically encoded indicator on a movable object that transmits geo-positional data, allowing for automatic camera calibration by decoding the indicator in video frames and applying geometric transformations to determine camera calibration data without manual readjustment, using either parallel or serial LED transmission modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual readjustment is performed to synchronize cameras and geo-positional data, then matching accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system uses the moving object's own indicator (e.g., license plate, logo) as the calibration target, eliminating the need for external calibration objects. The object's natural movement through the surveillance area provides continuous calibration data, making the calibration process self-service and automated.
Solution Approach 2:
The patent replaces manual mechanical adjustment of camera calibration with an automated optical recognition system. Image processing algorithms automatically detect the indicator in video frames and compute calibration parameters, substituting manual operations with automated computational processes.
2Ease of operation
If traditional calibration methods are used without synchronization, then operational simplicity is maintained, but calibration accuracy deteriorates
Solution Approach 1:
The patent introduces an indicator as an intermediary element that bridges the moving object and the camera system. This indicator serves as a common reference that both the object's geo-positional data and the camera's visual data can be matched against, enabling accurate calibration without complex synchronization protocols.
Solution Approach 2:
The system continuously captures video frames containing the indicator and compares the detected indicator position with the known geo-positional data. This feedback loop allows real-time computation and adjustment of camera calibration parameters, maintaining accuracy without manual intervention.
3Device complexity
If GPS-based location estimation is used, then device complexity is reduced, but position accuracy deteriorates
Solution Approach 1:
The patent merges multiple data sources including GPS coordinates, indicator recognition results, and camera image data into a unified calibration framework. By combining these complementary information sources, the system achieves position accuracy superior to GPS alone while maintaining reasonable system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and efficient matching of video data with geo-positional information, allowing for precise camera calibration without hardware modifications, reducing the need for manual adjustments and improving situational awareness in surveillance systems.
Implementation Method 1
The video data includes an optically encoded indicator associated with the movable object. A computer implemented method for determining camera calibration data includes: receiving geo-positional data of a moving object, wherein the geo-positional data is associated with an indicator; receiving a sequence of frames from the at least one camera, wherein at least one frame has a picture of the moving object with a structure and with an encoded version of the indicator which are optically recognizable; extracting the indicator associated with the at least one frame by decoding the optically encoded version of the indicator of the at least one frame
Data Source
AI summary
A computer implemented method, computer program product, and computer system for determining camera calibration data. The computer system receives geo-positional data of a moving object, wherein the geo-positional data is associated with an indicator (112). The computer system receives further a sequence of frames (140) from the at least one camera (150), wherein at least one frame has a picture of the moving object (118) with a structure and with an encoded version of the indicator which are optically recognizable. The indicator associated with the at least one frame is extracted by decoding (170) the optically encoded version of the indicator of the at least one frame. The geo-positional data of the moving object which is in the picture of the at least one frame is obtained by matching (172) the indicator associated with the geo-positional data of the moving object and the decoded indicator associated with the at least one frame. At least one reference point of the at least one frame is identified by analyzing the optically recognizable structure in the picture of the at least one frame. The camera calibration data of the at least one camera is determined by applying a geometric transformation (174) on the at least one reference point and its associated geopositional data of the moving object which is in the at least one frame.