Vehicle Camera Trailer Detection Using ROI Optical Flow
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Solution Overview
Problem
Accurate detection of trailer properties using image-processing-based perception is computationally intensive, leading to wasted processing power when no trailer is attached, which could be utilized for other purposes within the camera monitoring system.
Innovation Solution
A method involving identifying a region of interest within a video feed from multiple cameras, determining optical flow within this region, and matching it to a predetermined pattern to detect a trailer's presence, thereby reducing unnecessary computational load by limiting optical flow analysis to a specific area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image-processing-based perception is operated continuously to detect trailer properties, then detection accuracy is maintained, but processing power is wasted when no trailer is attached
Solution Approach 1:
The system performs preliminary detection using optical flow analysis on a region of interest before committing to full image-processing-based perception. This preliminary action identifies potential trailer presence, allowing the system to activate full detection only when necessary, thus avoiding continuous processing power waste while maintaining detection accuracy when trailers are present
Solution Approach 2:
The video feed is segmented into a region of interest and other areas. Optical flow analysis is applied only to the region of interest, which is a smaller subset of the full image. This segmentation reduces the computational load while maintaining the ability to detect trailers effectively, as trailers typically appear in specific regions of the camera view
2Reliability
If optical flow analysis is performed on the entire video feed, then comprehensive scene analysis is achieved, but computational load increases significantly
Solution Approach 1:
Different processing strategies are applied to different regions of the video feed. The region of interest receives full optical flow analysis for reliable trailer detection, while other regions receive minimal or no processing. This local quality approach maintains scene analysis reliability in critical areas while improving overall processing efficiency by reducing computational load in non-critical areas
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Efficiently detects trailer presence by minimizing unnecessary processing, saving computational resources and enabling effective utilization of these resources for other vehicle systems.
Implementation Method 1
determining an optical flow within the region of interest
Data Source
AI summary
A method for detecting a trailer presence includes identifying a region of interest within a video feed from one or more cameras secured to a vehicle. The video feed depicts a scene having a first pixel area, and the region of interest corresponds to a portion of the scene having a second pixel area that is less than the first pixel area. The method also includes determining an optical flow within the region of interest, and determining that a trailer is connected to the vehicle in response to the optical flow within the region of interest matching a predetermined pattern corresponding to a connected trailer. A camera monitoring system for a vehicle is also disclosed.