Image-Based Map Data Update Using Object Correlation
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Solution Overview
Problem
Current digital maps are not updated quickly enough due to the slow deployment rate of mapping vehicles equipped with expensive sensors, leading to delayed updates of road information such as lane changes, traffic signs, and road conditions.
Innovation Solution
A method and apparatus for object identification and location correlation based on images, using pattern recognition and timestamp correlation to determine the location of objects in images captured by cameras, allowing for real-time updates of map data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mapping vehicles with expensive sensors are deployed continuously to update digital maps, then the accuracy and completeness of map data is improved, but the cost and time required for updates increases significantly
Solution Approach 1:
The patent uses images captured by cameras as copies or representations of the actual road scene, allowing map updates to be performed using image data rather than requiring physical presence of mapping vehicles with sensors. This copying approach enables faster updates while maintaining accuracy.
Solution Approach 2:
The patent replaces the mechanical system of physical mapping vehicles traveling to collect sensor data with an automated image processing system. Cameras capture images and computational algorithms automatically extract road features, eliminating the need for continuous deployment of physical mapping vehicles.
2Productivity
If mapping vehicles are deployed less frequently to reduce costs, then operational expenses decrease, but the timeliness of map updates deteriorates
Solution Approach 1:
The system performs self-service by automatically processing captured images to extract road features, objects, and conditions. The computational pipeline autonomously identifies, detects, and updates map data without requiring manual intervention or repeated vehicle deployments, thereby maintaining timeliness while improving efficiency.
Solution Approach 2:
The patent changes the fundamental parameter of data collection from periodic physical surveys to continuous image capture and processing. By transforming map updates into an automated image analysis process, the system achieves both higher productivity and maintained timeliness simultaneously.
3Measurement precision
If traditional sensor-based mapping methods are used to ensure accurate road information, then measurement precision is maintained, but the complexity and cost of the system increases
Solution Approach 1:
The patent extracts only the essential visual information needed for map updates from the complex sensor suite by using cameras alone. This extraction approach isolates the critical function of road feature detection from unnecessary sensor complexity, achieving accuracy with simpler equipment.
Solution Approach 2:
The patent replaces expensive, complex sensors with relatively simple, inexpensive cameras. The system uses multiple standard cameras rather than costly specialized sensors, reducing both device complexity and cost while maintaining the capability to capture sufficient detail for accurate map updates.
Data Source
AI summary
A method, apparatus and computer program product are provided for object identification and location correlation based on received images. A method is provided including receiving identity data associated with an object derived from one or more of a plurality of images determining an identity of an object in one or more of the plurality of images, receiving location information associated with a camera which captured the plurality of images, and correlating the identified object with a location for each of the respective images of the plurality of images.