Drone Trajectory Coordinate Conversion Without Calibration
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Solution Overview
Problem
Conventional camera calibration methods for extracting vehicle trajectory data from traffic videos are complex and limited by the need for control points, making them inaccurate and difficult to apply in urban road networks.
Innovation Solution
A method and system that convert trajectory coordinates of moving objects without calibration using control points, by capturing video with a drone camera, extracting pixel coordinates, and transforming them into WGS84 coordinates using drone location, camera attitude, and intrinsic parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DLT camera calibration method is used to extract vehicle trajectory data, then trajectory data can be obtained, but the process becomes complex and measurement accuracy is limited by the need for control points and experimental fields
Solution Approach 1:
The patent extracts and eliminates the need for control points and experimental fields from the calibration process. By using drone location information, camera attitude information, and intrinsic parameters directly, the method removes the complex calibration steps while maintaining trajectory extraction capability, thus reducing device complexity without sacrificing measurement precision
Solution Approach 2:
The patent introduces an intermediary coordinate transformation model that directly converts pixel coordinates to geographic coordinates using drone metadata (location, attitude, intrinsic parameters). This intermediary model bypasses the traditional DLT calibration process, simplifying the overall system while maintaining accuracy through direct geometric transformation
2Adaptability or versatility
If DLT camera calibration method is used, then trajectory data can be extracted, but the method is greatly limited by the number and distribution of control points on road sections and road slopes
Solution Approach 1:
The patent creates a universal calibration-free method that works across different road conditions (flat roads, slopes, urban areas) without requiring specific control point distributions. The method uses drone metadata that is universally available in modern drone systems, making it adaptable to various application conditions while maintaining measurement precision through direct geometric transformation
Solution Approach 2:
The method enables the system to self-calibrate using inherently available data from the drone itself (location, attitude, intrinsic parameters) without requiring external control points or experimental fields. This self-service approach eliminates the limitations imposed by control point distribution and makes the system universally applicable to different road geometries and conditions
Data Source
AI summary
Provided is a method and system for converting trajectory coordinates of moving objects, including: capturing a video of moving objects by drone; extracting trajectory data of moving objects in pixel coordinate system; solving a representation of unit direction vector corresponding to target point in camera coordinate system in ECEF coordinate system based on location information of drone, attitude information of camera, and intrinsic parameter information of camera during capturing of each frame, and in combination with pixel coordinates of target point in pixel coordinate system, to obtain a representation of vector from ECEF origin to the target point; and, representing coordinates of target point in WGS84 coordinate system by using the representation of vector from the ECEF origin to the target point, and finally obtaining the coordinates of target point in WGS84 coordinate system based on target point altitude is the same as altitude at which the drone takes off.