Vehicle Detection ROI Adjustment for Curved Road Alignment
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Solution Overview
Problem
Existing vehicle detection systems face decreased accuracy when the shape of the road in front of the vehicle changes, leading to missed detections of vehicles due to misalignment of detection regions.
Innovation Solution
A vehicle detection device that adjusts its processing region based on changes in road shape, such as curvature or slope, and a light distribution control device that adapts the light distribution pattern accordingly to improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single camera is used for vehicle detection, then the device complexity is low, but the detection precision and reliability are insufficient
Solution Approach 1:
The patent divides the detection system into multiple independent camera units (first camera and second camera) positioned at different locations. Each camera captures images from its own perspective, and the control unit processes images from both cameras to detect vehicles. This segmentation approach improves detection precision by providing multiple viewing angles while keeping each camera unit relatively simple.
Solution Approach 2:
The patent combines the detection results from multiple cameras by having the control unit acquire images from both the first camera and second camera, then process them together to determine vehicle presence. This merging of multiple detection sources enhances reliability and precision without requiring each individual component to be overly complex.
2Reliability
If multiple cameras are used to improve detection reliability, then the detection reliability improves, but the device complexity and cost increase
Solution Approach 1:
The detection system is segmented into multiple camera units positioned at different locations (first camera and second camera), each independently capturing images. This segmentation improves reliability by providing redundant detection capabilities and multiple perspectives, while each camera unit remains a standard, manageable component.
Solution Approach 2:
Multiple cameras perform the same basic function of capturing images, but from different positions. The control unit universally processes images from any camera to detect vehicles, making the system reliable through redundancy without requiring specialized complex components for each camera.
3Area of stationary object
If cameras are positioned to capture wide areas, then the detection coverage increases, but the image quality and detection precision decrease
Solution Approach 1:
Instead of using a single camera with wide coverage that compromises image quality, the patent segments the coverage area into multiple zones captured by different cameras. Each camera focuses on a specific area with higher image quality, and the control unit combines these segmented views to achieve comprehensive detection coverage.
Solution Approach 2:
The patent transitions from a single-viewpoint detection approach to a multi-viewpoint approach by positioning cameras at different locations. This adds a spatial dimension to the detection system, allowing each camera to capture high-quality images of its specific zone while collectively covering a broader area through the combination of multiple perspectives.
Data Source
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AI summary
A vehicle detection device (6) performs detection of a vehicle in front within a processing region (ROI) set in an image (IMG) based on an imaging device (4) and displaces or transforms the processing region (ROI) based on a change in shape of a road in front.