Multi-faceted Image Projection onto Convex Polyhedron
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Solution Overview
Problem
Current sensor systems in vehicles, particularly in autonomous driving, face challenges in projecting and processing wide-angle images from fisheye cameras, which result in distorted images due to convex non-rectilinear appearances, limiting effective 360-degree coverage and accurate target classification.
Innovation Solution
A system and method that project a multi-faceted image onto a convex polyhedron by determining a mapping between pixels in a wide-angle image and a multi-faceted image using intrinsic camera parameters and pixel unit vectors, transforming fisheye camera images into a piece-wise projective image with fewer distortion, comprising at least three facets, to achieve a narrower field of view representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of moving object
If a wide-angle fisheye camera is used to achieve 360-degree coverage, then the field of view is improved, but image distortion increases due to convex non-rectilinear appearance
Solution Approach 1:
The patent divides the distorted wide-angle image into multiple regions or facets, each corresponding to a specific viewing angle range. By segmenting the image processing task, the system applies different correction transformations to different regions, effectively reducing overall distortion while maintaining 360-degree coverage capability
Solution Approach 2:
The patent transforms the image from a conventional 2D plane to a multi-faceted 3D representation projected onto a convex polyhedron. This dimensional transformation allows the system to represent wide-angle views with reduced distortion by mapping pixels to faceted surfaces rather than flat planes
2Manufacturing precision
If a mapping transformation is applied to reduce image distortion, then image quality is improved, but processing complexity increases
Solution Approach 1:
The patent pre-calculates and stores mapping tables that define the transformation relationships between wide-angle image coordinates and multi-faceted projected coordinates. During actual processing, the system simply looks up pre-computed values rather than performing complex real-time calculations, significantly reducing processing complexity
Solution Approach 2:
The patent transforms the image coordinate system by changing parameters such as projection angle, facet orientation, and pixel mapping relationships. By adjusting these parameters, the system optimizes the balance between distortion reduction and processing efficiency for different application scenarios
Data Source
AI summary
Systems and methods for projecting a multi-faceted image onto a convex polyhedron based on an input image are described. A system can include a controller configured to determine a mapping between pixels within a wide-angle image and a multi-faceted image, and generate the multi-faceted image based on the mapping.