Geoposition Estimation Using 2D Camera and Spatial Model
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Solution Overview
Problem
Current systems for determining geoposition from two-dimensional images are inadequate for certain applications, necessitating advancements in technology to accurately and efficiently convert 2D camera images into geospatial data.
Innovation Solution
A system that pairs 2D camera images with spatial datasets using an image-position model, leveraging LiDAR or other spatial sensors to estimate physical measurements and geoposition by aligning camera images with spatial information, allowing for the calculation of 3D coordinates and tracking of objects across different camera views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If 2D camera images are used to determine geoposition, then the system is simple and cost-effective, but the measurement precision and reliability are insufficient
Solution Approach 1:
The patent introduces an image-position model as an intermediary that maps 2D image coordinates to 3D world coordinates. This model acts as a bridge between the simple 2D camera data and the required accurate geoposition information, enabling precise location determination without complex 3D sensing hardware.
Solution Approach 2:
The patent transforms 2D image data into 3D geoposition information by introducing a dimensional transformation through the image-position model. This allows the system to extract depth and spatial information from inherently two-dimensional camera images, achieving accurate geoposition determination.
2Measurement precision
If spatial datasets from LiDAR are integrated with 2D camera images, then geoposition accuracy is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent merges 2D camera images with spatial datasets from LiDAR or other spatial sensors into a unified image-position model. This combination allows the system to leverage the complementary strengths of both data sources, achieving high-precision geoposition determination while maintaining a cohesive system architecture.
Solution Approach 2:
The image-position model serves multiple functions: it processes both 2D camera images and spatial datasets, performs coordinate transformations, and outputs geoposition information. This multi-functionality reduces the need for separate processing pipelines for different sensor types, managing system complexity.
3Reliability
If multiple camera views are used for object tracking, then re-identification accuracy improves, but the processing time and computational load increase
Solution Approach 1:
The patent pre-establishes the image-position model with spatial relationships and calibration data before actual tracking occurs. This preliminary setup allows the system to perform rapid geoposition calculations during real-time tracking without repeated complex computations, reducing processing time while maintaining accuracy across multiple camera views.
Data Source
AI summary
A tracking system is used to determine geoposition of an object, such as a person, using images from a 2-D camera, in which pixels in the 2-D image have been assigned a 3-D position by pairing the camera image with a spatial model. A spatial model can be provided by a suitable 3-D imaging device, such as but not limited to a LiDAR system, though other types of spatial imagers are contemplated. The tracking system can use geoposition data to aid in reidentification of a person across multiple cameras, as well as determine behavior of people that are being tracked.