Automated Stereo Image Association via GPS Pass Points
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Solution Overview
Problem
Manual stereo image acquisition in photogrammetry is inefficient due to difficulties in maintaining consistent camera height and tilting angles, requiring skilled manual selection and matching of pass points, which is time-consuming and prone to errors.
Innovation Solution
A method and system that automate stereo-matching by using an image pickup device, GPS unit, and azimuth sensor to set up pass points, compare and identify them across frames, and calculate 3-dimensional data, facilitating efficient and accurate association of images taken from different points while moving, with high-resolution images at initial and final points and low-resolution images during movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual image acquisition is used, then flexibility in image taking is maintained, but maintaining consistent camera height and tilting angles is difficult and time-consuming
Solution Approach 1:
The patent replaces manual mechanical control of camera parameters with an automated image pickup device that controls camera height, tilting angles, and image acquisition based on GPS position and pre-stored image information, eliminating manual operation while maintaining parameter consistency
Solution Approach 2:
The system automatically determines camera parameters and image acquisition settings based on GPS position data and pre-stored information, allowing the system to serve itself without manual intervention for parameter determination
2Measurement precision
If manual selection and matching of pass points is performed, then accuracy can be maintained, but the process is time-consuming and requires high skill
Solution Approach 1:
The system automatically identifies and matches pass points between images by retrieving pass point information from pre-stored data and automatically associating images based on GPS position and image parameters, eliminating manual selection and matching operations
Solution Approach 2:
Pass point information is pre-stored in the memory along with image information before the actual measurement process, allowing the system to retrieve and use this information automatically during image association without manual intervention
3Adaptability or versatility
If images are taken with different camera parameters, then adaptability to different positions is improved, but stereo-matching becomes more difficult and requires more pass points
Solution Approach 1:
The system uses GPS position information and pre-stored image parameters as feedback to automatically determine appropriate camera parameters for each image, ensuring consistent parameters are used while maintaining the ability to take images from different positions
Solution Approach 2:
The system automatically adjusts camera parameters based on GPS position and pre-stored information, changing parameters adaptively to different positions while maintaining consistency within the measurement process, thus balancing flexibility with stereo-matching simplicity
Data Source
AI summary
A method for associating a stereo image, by acquiring images of an object from a first point and a second point and by associating the image at the first point and the second point, comprising a step of moving from the first point to the second point while taking an image of the object, a step of setting two or more pass points on the image of the first point, a step of comparing a preceding image and a subsequent image over time, a step of retrieving and identifying the pass points of the preceding image in the subsequent image, a step of retrieving and identifying the pass points sequentially with respect to every frame image data from the image of the first point to the image of the second point, a step of identifying the pass points of the image of the second point, and a step of associating the image at the first point with the image at the second point via the pass points.