Autonomous Driving Image Correction Using Past Reference Frames
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Solution Overview
Problem
Existing autonomous driving systems face challenges in maintaining accurate image recognition due to environmental changes such as weather conditions and lighting, which can lead to decreased safety and reliability in navigation.
Innovation Solution
An information processing device that infers and corrects images in real-time using a database of past images taken under similar conditions, reducing environmental influences like fog, haze, and backlight to generate clearer images for navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If image recognition is performed using real-time images under changing environmental conditions, then the system can respond to current situations, but image quality deteriorates due to weather, lighting, and other environmental factors
Solution Approach 1:
The system pre-acquires images taken under various environmental conditions and stores them in advance. When the current image quality deteriorates due to environmental factors, the system retrieves and uses the pre-acquired reference image taken under similar conditions, thereby maintaining recognition accuracy without needing to capture high-quality images in real-time adverse conditions.
Solution Approach 2:
The system creates a copy of the reference image taken under favorable environmental conditions and uses this copied image for recognition when current imaging conditions are poor. This allows the system to bypass the limitation of real-time image quality by utilizing a replicated version of the scene captured when conditions were optimal.
2Measurement precision
If the system uses pre-acquired reference images to maintain image quality, then recognition accuracy improves, but the system complexity increases due to additional image storage and matching requirements
Solution Approach 1:
The system performs self-service by automatically acquiring, storing, and managing its own reference images without requiring external intervention. The image acquisition unit captures images during normal operation, and the storage unit automatically archives them, allowing the system to maintain its own reference library autonomously and reducing the need for additional dedicated hardware or manual setup.
Solution Approach 2:
The image acquisition unit serves multiple functions: it captures images for real-time recognition and simultaneously acquires images for building the reference image database. This multi-functionality reduces the need for separate dedicated systems for reference image collection, thereby limiting the increase in overall system complexity while maintaining recognition accuracy.
Data Source
AI summary
An information processing device according to the present disclosure includes an inference unit that infers, on the basis of a result of checking a first image against a plurality of images taken in the past, a third image that is an image taken in the past at a position corresponding to a second image to be taken at a next timing of the first image, and a generation unit that generates a fourth image that is an image obtained by correcting the second image on the basis of the third image in a case where the second image is acquired.