Fisheye Image Overlap Ambiguity Resolution
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Solution Overview
Problem
Vehicle-mounted camera systems with fisheye lenses face issues of image ambiguity and invisibility of objects in overlapping regions, leading to safety concerns due to duplicated or missing representations of pedestrians and other objects in the vehicle's surroundings.
Innovation Solution
An in-vehicle computing system that captures fisheye images from adjacent cameras, identifies moving objects in overlapping regions, and modifies the projected images onto a virtual bowl-shaped projection surface to ensure clear visualization of objects, preventing duplication and invisibility by adjusting the contour projection and junctions between adjacent images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If fisheye cameras with overlapping fields of view are used to capture vehicle surroundings, then the coverage area is improved, but image ambiguity and object duplication occur in overlapping regions
Solution Approach 1:
The patent segments the overlapping region into multiple sub-regions and processes each sub-region separately using different compositing methods. This divides the problematic overlapping area into manageable parts, allowing different handling strategies for different portions of the overlap, thereby reducing image ambiguity while maintaining comprehensive coverage.
Solution Approach 2:
The patent applies different compositing methods to different sub-regions of the overlapping area based on local characteristics. By tailoring the compositing approach to specific local conditions rather than applying a uniform method across the entire overlapping region, the system optimizes object visualization and reduces ambiguity in each local area.
2Reliability
If multiple cameras are used to capture all surroundings, then the visibility of vehicle surroundings is improved, but the complexity of the camera system increases
Solution Approach 1:
The patent merges images from multiple cameras through a compositing process that combines overlapping regions into a unified bowl-shaped projection. This merging approach allows the system to use multiple cameras for comprehensive coverage while processing the images to present a unified view, effectively managing the complexity of having multiple camera inputs.
Solution Approach 2:
The patent creates a universal bowl-shaped projection surface that can accommodate and integrate images from multiple cameras with different fields of view. This multi-functional projection surface serves as a common framework for combining data from various camera sources, simplifying the overall system architecture despite using multiple cameras.
3Ease of operation
If overlapping regions are processed with standard compositing methods, then image integration is simplified, but objects may become invisible or duplicated
Solution Approach 1:
The patent employs dynamic compositing methods that adapt to the specific characteristics of objects and regions in the overlapping area. Rather than using static, uniform processing, the system dynamically adjusts compositing parameters and methods based on local conditions, maintaining both processing efficiency and object detection reliability.
Solution Approach 2:
The patent incorporates feedback mechanisms that monitor the compositing process and adjust processing methods based on detected objects and their characteristics. This feedback loop ensures that objects are properly visualized by adapting the compositing approach according to what is actually present in the overlapping regions, preventing both invisibility and duplication.
Data Source
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AI summary
Technologies for visualizing moving objects on a bowl-shaped image include a computing device to receive a first fisheye image generated by a first fisheye camera and capturing a first scene and a second fisheye image generated by a second fisheye camera and capturing a second scene overlapping with the first scene at an overlapping region. The computing device identifies a moving object in the overlapping region and modifies a projected overlapping image region to visualize the identified moving object on a virtual bowl-shaped projection surface. The projected overlapping image region is projected on the virtual bowl-shaped projection surface and corresponds with the overlapping region captured in the first and second fisheye images.