Camera Operation Assessment via Feature Vector Similarity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles face challenges in assessing the operation of cameras, particularly in determining if cameras are functioning properly or if issues like debris, condensation, or non-functioning pixels are present, which is critical for making driving decisions.
Innovation Solution
A method involving processors that receive images from multiple cameras with overlapping fields of view, reduce and analyze these images to generate feature vectors, calculate similarity scores, and compare them to thresholds or track changes over time to assess camera operation, triggering responses such as cleaning or requesting remote assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If images are captured by multiple cameras with overlapping fields of view for assessment, then camera operation reliability is improved, but device complexity increases
Solution Approach 1:
The patent uses multiple cameras to capture images of the same scene, creating redundant copies of visual information. By comparing these copied images, the system can assess camera operation reliability without adding complex assessment hardware. The overlapping fields of view ensure that the same objects are captured by multiple cameras, enabling reliability assessment through image comparison.
2Measurement precision
If feature vectors are generated and similarity scores calculated to assess camera operation, then measurement precision is improved, but computational complexity increases
Solution Approach 1:
The patent extracts key features from captured images by generating feature vectors that represent essential visual information. Instead of comparing entire images, the system extracts and compares specific features (such as object characteristics, positions, and attributes), which improves assessment precision while reducing computational complexity by focusing only on relevant image components.
3Speed
If images are reduced and cropped to overlapping field of view before analysis, then processing speed is improved, but information loss increases
Solution Approach 1:
The patent applies different processing strategies to different parts of the image data. By cropping images to their overlapping fields of view, the system focuses computational resources on the regions where both cameras captured the same scene. This local quality approach processes only the relevant overlapping portions in detail while reducing or discarding non-overlapping regions, thereby improving processing speed without significantly losing information needed for camera assessment.
Data Source
AI summary
The disclosure relates to assessing operation of two or more cameras. These cameras may be a group of cameras of a perception system of a vehicle having an autonomous driving mode. A first image captured by a first camera and a second image captured by a second camera may be received. A first feature vector for the first image and a second feature vector for the second image may be generated. A similarity score may be determined using the first feature vector and the second feature vector. This similarity score may be used to assess the operation of the two cameras and an appropriate action may be taken.