Parking Lane Arrow Detection Using Top-Down Vision
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Solution Overview
Problem
Modern vehicles lack the capability to accurately determine lane directions in parking zones based on ground markings, relying on GPS data and low-resolution sensors that are not always reliable, especially in dynamic environments.
Innovation Solution
Implement a camera-based system using machine learning models to detect and analyze ground arrow markings, generating a top-down view and performing point density analysis to determine the correct lane direction, providing real-time navigation assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS data and low-resolution sensors are used to determine lane direction, then the system can operate with simpler hardware, but the measurement precision and reliability deteriorate in dynamic environments
Solution Approach 1:
The patent replaces traditional mechanical/sensor-based detection systems with a computer vision system using cameras and image processing algorithms. The system captures images of ground markings, generates top-down views through geometric transformations, and detects lane directions using image analysis techniques, substituting physical sensors with optical detection and computational methods.
2Reliability
If traditional sensors are used for navigation, then the device complexity is reduced, but the reliability deteriorates in parking zones
Solution Approach 1:
The patent introduces an intermediary processing layer that transforms raw camera images into top-down view representations before performing lane direction detection. This intermediary step involves geometric transformations and image generation processes that mediate between the raw visual data and the final navigation decisions, improving reliability by creating a more suitable representation for analysis.
3Measurement precision
If high-resolution image capture and image analysis are implemented, then the measurement precision improves, but the loss of time increases due to processing requirements
Solution Approach 1:
The patent performs preliminary actions by generating top-down view images and pre-processing the visual data before the actual lane direction detection takes place. By preparing the image data in advance through geometric transformations and creating optimized representations, the system reduces the computational burden during real-time detection, thereby reducing processing time while maintaining high precision.
Data Source
AI summary
A method performed by a computing device configured to detect a lane direction in a parking zone being navigated by a vehicle includes capturing, using an image capture device, at least one image of an environment surrounding the vehicle that includes an arrow marking on a ground surface of the parking zone, generating a top-down image, including the arrow marking, of the environment surrounding the vehicle based on the captured at least one image, performing an image analysis of the top-down image to determine an arrow direction of the arrow marking, detecting, based on results of the image analysis, the lane direction of a lane occupied by the vehicle based on the determined arrow direction, generating and providing an output indicating the lane direction of the lane occupied by the vehicle.