Vehicle Imaging System for Object Categorization via Relative Motion Analysis
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Solution Overview
Problem
Existing vehicle exterior light control systems struggle to accurately distinguish between oncoming or preceding vehicles and other objects, especially when they are off-center or on curves, leading to difficulties in preventing glare while maintaining effective illumination.
Innovation Solution
An imaging system that analyzes image frame data to detect dominant scene motion and categorize objects based on relative motion, allowing for more accurate identification of vehicles on traffic circles, roundabouts, or intersecting roads, and adjusting light beams accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing vehicle exterior light control systems use traditional object detection methods, then they can identify oncoming or preceding vehicles, but they fail to accurately distinguish vehicles from other objects when they are off-center or on curves
Solution Approach 1:
The system dynamically adapts to different scene conditions by detecting dominant motion patterns in the image sequence and adjusting object classification accordingly. Instead of using fixed detection thresholds, the system modifies its behavior based on whether objects are moving with or against the dominant scene motion, enabling accurate identification of vehicles on curves or off-center positions
Solution Approach 2:
The system changes the parameter used for object classification from static spatial features to dynamic motion-relative features. By calculating motion vectors and comparing object motion to dominant scene motion, the system transforms the classification criterion from position-based to motion-based, improving accuracy in non-standard driving scenarios
2Illumination intensity
If the system uses high beam illumination to maintain effective lighting, then visibility is improved, but glare is caused to other drivers
Solution Approach 1:
The system continuously monitors the scene using image capture and processes sequences of images to detect moving objects. Based on the feedback from object detection and classification, the control system dynamically adjusts headlamp operation between high beam and low beam modes, maintaining visibility while preventing glare to other drivers
Solution Approach 2:
The headlamp control system dynamically switches between high beam and low beam illumination based on real-time detection of vehicle presence and classification. The illumination intensity is not fixed but adapts continuously according to the detected scene conditions, ensuring effective lighting when safe and preventing glare when other vehicles are present
Data Source
AI summary
An imaging system is provided for a vehicle. The imaging system includes: an imager configured to image a forward external scene of the controlled vehicle and to generate image frame data corresponding to each frame of a series of acquired image frames; and a processor configured to receive and analyze the image frame data to detect a dominant scene motion and to determine relative motion of objects as compared to the dominant scene motion, and wherein the analysis of the image frame data performed by the processor includes categorizing objects detected in the image frame data using the relative motion of those objects.