Under-Vehicle View Rendering with Motion Data and Stored Images
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Solution Overview
Problem
Existing vehicle surround view systems lack coverage of areas not within the field of view of cameras and are hindered by camera failures, necessitating improved sensor fusion and perceptually enhanced techniques.
Innovation Solution
A technique for rendering an under-vehicle view by capturing images with a set of cameras around the vehicle, storing them with associated timestamps, determining vehicle motion, and using motion data to generate and output a rendered view based on stored images and motion data, employing a GPU for image processing and rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple cameras are used to provide external views around the vehicle, then the coverage area and reliability are improved, but the device complexity and cost increase
Solution Approach 1:
The patent creates a virtual copy of the camera system by generating a synthetic under-vehicle view through image processing and rendering. Instead of installing additional physical cameras underneath the vehicle, the system processes images from existing cameras to create a virtual representation of the under-vehicle area, thereby maintaining reliability without increasing hardware complexity
Solution Approach 2:
The patent introduces an image processing and rendering system as an intermediary between the physical cameras and the final surround view output. This intermediary processes images from multiple cameras, applies motion compensation, and generates the under-vehicle view, allowing the system to achieve enhanced coverage without directly adding more cameras
2Area of stationary object
If images are captured and stored with timestamps for later rendering, then the under-vehicle view coverage is improved, but the memory requirements and processing time increase
Solution Approach 1:
The patent performs preliminary actions by capturing and timestamping images from multiple cameras as the vehicle moves. These images are stored in memory with their capture times recorded, enabling later retrieval and processing to generate the under-vehicle view without requiring continuous high-rate sampling
Solution Approach 2:
The patent uses partial action by selectively processing only the necessary images from the captured set. Instead of processing all captured images continuously, the system retrieves and processes only those images that are needed for the current under-vehicle view generation, reducing memory bandwidth and processing requirements
3Measurement precision
If motion data is used to generate the under-vehicle view from stored images, then the accuracy of the rendered view is improved, but the processing complexity increases
Solution Approach 1:
The patent incorporates feedback by using motion data (from GPS, IMU, or wheel speed sensors) to compensate for vehicle movement when generating the under-vehicle view. The system continuously monitors vehicle position and orientation changes and uses this feedback to adjust the rendering of stored images, maintaining accuracy despite vehicle motion
Solution Approach 2:
The patent replaces mechanical solutions with computational methods. Instead of using complex mechanical stabilization systems or additional sensors to physically track vehicle motion, the system substitutes these with software-based motion compensation algorithms that process motion data and adjust image rendering accordingly
Data Source
AI summary
A technique for rendering an under-vehicle view including obtaining a first location of a vehicle, the vehicle having a set of cameras disposed about the vehicle, capturing a set of images; storing images of the set of images in a memory, wherein the images are associated with a time the images were captured, moving the vehicle to a second location, obtaining the second location of the vehicle, determining an amount of time for moving the vehicle from the first location to the second location, generating a set of motion data, the motion data indicating a relationship between the second location of the vehicle and the first location of the vehicle, obtaining one or more stored images from the memory based on the determined amount of time, rendering a view under the vehicle based on the one or more stored images and set of motion data, and outputting the rendered view.