Vehicle-Mounted Camera Alignment via Image Overlay Guidance
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Solution Overview
Problem
Existing location-based services face challenges in obtaining accurate and relevant imagery data from vehicles due to poor camera alignment, leading to capture of off-road scene imagery such as sky or vehicle hood, which is not suitable for digital map making.
Innovation Solution
A computer-implemented method and apparatus that determines an optimal alignment of a device mounted in a vehicle by receiving image data, presenting an alignment template as an overlay, and processing the data to ensure the device captures images relevant for map making through machine learning and computer vision systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the device is mounted in the vehicle without alignment guidance, then the installation process is simple and quick, but the camera captures off-road scene imagery (sky, hood) that is not suitable for map making
Solution Approach 1:
The system uses the device's own camera to capture images and generates alignment guidance automatically based on image processing, eliminating the need for external alignment tools or manual calibration equipment. The device self-diagnoses its alignment status and provides self-correction guidance.
Solution Approach 2:
The patent replaces manual mechanical alignment procedures with automated image processing and computer vision algorithms. Instead of using physical alignment tools or manual adjustment mechanisms, the system uses software-based image analysis to detect misalignment and guide correction.
2Manufacturing precision
If manual alignment adjustment is performed, then the device can be positioned, but it requires user expertise and time-consuming trial and error
Solution Approach 1:
The system captures images through the camera, processes them to detect alignment status, and provides real-time feedback through alignment guidance overlays. This closed-loop feedback mechanism allows users to see immediately whether adjustments are improving alignment, eliminating trial-and-error guessing.
Solution Approach 2:
The system performs preliminary image capture and analysis to generate alignment guidance before the user makes any physical adjustments. By pre-calculating the correct alignment direction and displaying guidance overlays in advance, the system prepares the user for precise adjustment without requiring multiple iterative attempts.
3Productivity
If the device alignment is not monitored during vehicle movement, then the system operates continuously without interruption, but vehicle movement causes the device to shift from its optimal alignment
Solution Approach 1:
The system periodically recaptures images and re-evaluates alignment status during vehicle operation. Instead of continuous monitoring that would consume excessive resources, the system performs alignment checks at regular intervals or when triggered by motion detection, balancing productivity with reliability.
Solution Approach 2:
The alignment guidance system is designed to be dynamic and adaptive, allowing the device to be re-aligned during vehicle operation. The system can detect shifts caused by vehicle movement and provide updated guidance to restore optimal alignment, making the system adaptable to changing conditions during operation.
Data Source
AI summary
An approach is provided for determining an optimal alignment of a device. The approach, for example, involves receiving image data from a device mounted in a vehicle. The approach also involves presenting an alignment template in a user interface of the device as an overlay on the image data, wherein the alignment template provides one or more guidelines indicating a target alignment of the device to capture images from the vehicle for an application. The approach further involves processing the image data against the alignment template to determining an alignment of the device in relation to the target alignment.