Vehicle Blind Spot Visualization Using Virtual Viewpoints
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Solution Overview
Problem
Existing vehicle safety technologies are costly and complex, and fail to effectively address the blind spots caused by vehicle pillars, leading to potential traffic accidents due to the driver's inability to see objects within these obscured areas.
Innovation Solution
A method utilizing real-time image data acquisition, 3D mapping, and Simultaneous Localization and Mapping (SLAM) technology to create a 3D map of the vehicle's environment and compartment, determining the blind spot regions, and detecting environmental information within these areas to alert the driver of potential hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time image data acquisition and 3D mapping are implemented to visualize blind spots, then driver safety is improved, but device complexity and implementation cost increase
Solution Approach 1:
The patent applies multi-functionality by using the existing front-facing camera primarily for forward viewing, and secondarily for blind spot detection by processing images through virtual viewpoint generation algorithms. This allows one device to serve multiple purposes, reducing the need for additional dedicated sensors while maintaining safety benefits
Solution Approach 2:
The patent creates virtual copies of the scene from different viewpoints by generating virtual images from the front camera data. These virtual images represent blind spot areas without requiring physical cameras in those locations, reducing hardware complexity while providing comprehensive coverage
2Measurement precision
If multiple cameras are installed to cover blind spot areas, then detection accuracy is improved, but manufacturing cost and installation complexity increase
Solution Approach 1:
The patent extracts and removes the need for physical cameras in blind spot locations by generating virtual images computationally from front camera data. This extraction of the imaging function from physical hardware to computational processing reduces installation cost and complexity while maintaining detection capability
Solution Approach 2:
The patent replaces the mechanical system of multiple physical cameras with a computational image processing system. By using algorithms to generate virtual viewpoints from front camera images, the system substitutes hardware complexity with software processing, reducing manufacturing and installation costs
3Strength
If the width of A pillars is increased to improve structural strength, then vehicle safety is improved, but the blind spot area increases reducing driver visibility
Solution Approach 1:
The patent introduces virtual images as an intermediary representation of blind spot areas. These virtual images provide visual information about objects that would otherwise be completely hidden behind pillars, mediating between the structural need for pillars and the driver's need for visibility
Solution Approach 2:
The system provides feedback to the driver by displaying virtual images of blind spot areas on the dashboard or windshield. This feedback loop allows the driver to see objects in areas that would otherwise be obscured by necessary structural pillars, maintaining both structural integrity and situational awareness
Data Source
AI summary
The present disclosure provides a method, a device, a terminal, a system and a vehicle for visualization of vehicle's blind spot. The method includes: acquiring real-time image data in front of the vehicle; creating a Three-Dimension (3D) map with the acquired image data; determining a current location of the vehicle in the 3D map; acquiring the relative location information between the driver and the sight-blocking object that blocks the vision of the driver; determining the blind spot in the vision of the driver in connection with structure information of the sight-blocking object and the relative location information between the driver and the sight-blocking object that blocks the vision of the driver; and determining environmental information of the blind spot in the vision in accordance with the 3D map, the current location of the vehicle in the 3D map and the blind spot in the vision of the driver.