Image Distance Measurement with Roll Tilt Correction
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Solution Overview
Problem
Conventional image-based distance measurement methods for personal mobility vehicles, such as electric kickboards and motorcycles, are inaccurate due to significant rotation in the roll direction, leading to errors in measuring distances between moving and target objects.
Innovation Solution
A method and apparatus that acquire a driving image, calculate tilt information using a 3-axis sensor, correct the image based on this information, and use a neural network model to recognize and measure the distance to a target object, employing either image rotation or bounding box correction to minimize errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image-based distance measurement methods are applied to personal mobility, then the system can provide distance measurement functionality, but the measurement precision deteriorates due to significant roll rotation errors
Solution Approach 1:
The patent replaces the conventional mechanical assumption of fixed camera orientation with a sensor-based detection system. A 3-axis sensor detects the actual roll angle of the moving object, and this information is used to computationally correct the image data, substituting physical stability with sensor-based compensation.
Solution Approach 2:
The patent changes the parameter of image orientation by calculating a corrected image based on detected roll angle information. The correction process transforms the original image coordinates into a corrected coordinate system that compensates for the roll rotation, thereby maintaining measurement precision despite vehicle tilting.
2Measurement precision
If image correction based on tilt information is applied, then distance measurement precision improves, but device complexity increases due to additional sensors and processing
Solution Approach 1:
The patent makes the 3-axis sensor serve multiple functions: it detects roll angle for image correction, and can also provide orientation information for other navigation and safety functions. This multi-functionality justifies the added component by providing multiple benefits from a single sensor addition.
Solution Approach 2:
The patent introduces an image correction module as an intermediary between the raw image data and the distance measurement process. This module uses roll angle information to transform image coordinates before distance calculation, acting as a bridge that reconciles the conflicting requirements of simple hardware and accurate measurement.
3Measurement precision
If real-time image correction is performed, then accurate distance measurement is achieved during motion, but processing time increases
Solution Approach 1:
The patent performs preliminary action by pre-calculating the correction parameters based on roll angle detection, and applying these corrections to the image coordinate system before target object detection. This preparation step ensures that subsequent distance measurements can be performed accurately without requiring complex real-time corrections during the measurement process itself.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables accurate distance measurement between a moving object and a target object, even in environments with significant roll rotation, by correcting for tilt-induced errors, thereby enhancing safety and guidance in personal mobility scenarios.
Implementation Method 1
The tilt information may be calculated based on a rotation value of a 3-axis sensor in a roll direction.
Data Source
AI summary
There is provided a method for measuring a distance using a processor. The method for measuring a distance using a processor includes acquiring a driving image of a moving object, acquiring tilt information according to driving of the moving object, correcting the driving image by using the tilt information to calculate a distance between a target object included in the driving image and the moving object, and calculating a distance between the moving object and the target object based on the corrected driving image.