Camera Wing Position Detection Using Image Feature Tracking
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Solution Overview
Problem
Existing camera wing systems in commercial vehicles may fail to unfold correctly due to obstruction or motor failure, necessitating a method to automatically determine if the camera wings have reached their target positions without driver input.
Innovation Solution
A method and system using image processing to determine whether a camera wing has reached a target position by analyzing a series of images captured as the wing rotates, employing algorithms like SURF or SIFT to identify features and calculate the distances traveled by these features, comparing the sum of distances to predefined thresholds to confirm the wing's position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If image processing algorithms are used to determine wing position, then hardware complexity is reduced, but processing time increases
Solution Approach 1:
The system captures multiple images during the wing rotation process before final position determination is needed. By preparing the image sequence in advance during rotation, the actual position determination can quickly compare against pre-captured images, reducing the time penalty of image processing.
Solution Approach 2:
The patent replaces traditional mechanical position sensors (encoders, potentiometers) with image processing algorithms. SURF/SIFT feature extraction and optical flow analysis substitute for mechanical measurement systems, eliminating the need for additional hardware sensors while determining wing position through computational methods.
2Measurement precision
If multiple images are analyzed to determine wing position, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system extracts only the essential SURF or SIFT features from each image that are relevant to determining wing position. By selecting and tracking specific keypoints rather than processing entire images, the system achieves high measurement precision while reducing computational complexity to manageable levels.
Solution Approach 2:
The patent uses feature matching between consecutive images to create a virtual model of wing position changes. By copying and comparing feature points across images rather than analyzing full image data, the system achieves accurate position measurement with reduced processing requirements.
3Measurement precision
If feature tracking is used to monitor wing rotation, then position detection accuracy improves, but processing energy increases
Solution Approach 1:
The patent replaces energy-intensive continuous image processing with efficient feature-based tracking. By using SURF/SIFT algorithms that identify stable keypoints and tracking only these features across frames rather than processing full images, the system maintains high position detection accuracy while significantly reducing computational energy consumption.
Data Source
AI summary
A method for a camera monitor system (CMS) includes determining whether a wing has reached a target position. The wing is mounted to a vehicle, supports a camera, and is rotatable between an initial position and the target position. The determining is based on a plurality of images recorded by the camera in conjunction with the wing rotating from the initial position towards the target position. A camera monitor system (CMS) and a method for a camera monitor system (CMS) are also disclosed.