Two-Wheeler Inclination Detection via Width Minimization
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Solution Overview
Problem
Existing systems fail to accurately detect the inclination angle of a two-wheeler relative to the ground from images, which is crucial for predicting its motion and ensuring safe vehicle travel.
Innovation Solution
An apparatus using a processor to input images into a first classifier to detect a two-wheeler, rotate the object region by different angles, and determine the inclination angle by minimizing the width of the two-wheeler in rotated characteristic regions, with a second classifier confirming the positions of the two-wheeler's ends to calculate the optimal rotation angle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the inclination angle is detected using mean column values of pixels in fixed lines, then the detection process is simple, but the detection precision is insufficient
Solution Approach 1:
The system dynamically rotates the object region by different angles to generate multiple characteristic regions, then selects the rotation angle that minimizes the width of the two-wheeler. This dynamic approach adapts to varying inclination angles and improves detection precision compared to fixed-line methods.
Solution Approach 2:
The system changes the rotation angle parameter to generate multiple characteristic regions at different rotation angles (e.g., -30°, -15°, 0°, 15°, 30°). By varying this parameter and selecting the optimal value that minimizes width, the system achieves higher precision in inclination angle detection.
2Measurement precision
If multiple characteristic regions are generated by rotating the object region, then the inclination angle detection precision is improved, but the device complexity increases
Solution Approach 1:
The system segments the detection process by dividing it into distinct stages: object detection, rotation to generate characteristic regions, width detection for each region, and curve fitting. This segmentation makes the complex process more manageable and systematic.
Solution Approach 2:
The system replaces complex mechanical or manual measurement methods with automated image processing and curve fitting algorithms. The processor automatically performs rotation, width detection, and mathematical optimization to determine the inclination angle, reducing manual intervention and improving consistency.
3Measurement precision
If curve fitting is performed to determine the optimal rotation angle, then the detection accuracy is improved, but the computation time increases
Solution Approach 1:
The system performs preliminary actions by generating multiple characteristic regions at predetermined rotation angles before performing curve fitting. This pre-computation of candidate regions at reasonable angles narrows the search space and makes the subsequent optimization more efficient.
Solution Approach 2:
The curve fitting process serves multiple functions: it models the relationship between rotation angle and width, identifies the minimum width point, and provides a smooth continuous solution. This multi-functional approach achieves high accuracy without requiring exhaustive brute-force searches.
Data Source
AI summary
An apparatus for detecting an inclination angle includes a processor configured to input an image generated by a camera into a first classifier that has been trained to detect a two-wheeler, thereby detecting an object region including the two-wheeler in the image; rotate the object region by predetermined different angles to define characteristic regions as respective rotated regions; cut out the characteristic regions from the image; and detect a width of the two-wheeler in each of the characteristic regions and detects a rotation angle relative to the image as the inclination angle of the two-wheeler to the normal of the ground, based on rotation angles of the respective characteristic regions relative to the image and widths of the two-wheeler in the respective characteristic regions, the rotation angle minimizing the width of the two-wheeler.