Vehicle Type Identification via Real-Space Dimension Estimation
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Solution Overview
Problem
Existing vehicle type identification technologies face challenges in accurately distinguishing between vehicles of similar sizes, such as trucks and small vehicles, due to similarities in their appearance, leading to difficulties in precise identification.
Innovation Solution
A vehicle type identification device that estimates vehicle width, length, and height based on detected feature points from a captured image, using techniques such as calculating ground points and minimum ground clearance points, and then uses these dimensions to identify the vehicle type, enhancing accuracy by considering real-space measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If vehicle type identification is based on vehicle region size from captured images, then the identification process can be simplified, but the accuracy deteriorates because vehicles with similar appearance sizes cannot be distinguished
Solution Approach 1:
The patent transitions from two-dimensional image region analysis to three-dimensional spatial dimension analysis by calculating actual vehicle dimensions (length, width, height) based on detected feature points and ground clearance information. This dimensional transformation enables accurate distinction between vehicles with similar appearance sizes but different actual dimensions, such as trucks without loads versus small vehicles like station wagons.
Solution Approach 2:
The patent introduces ground clearance information as an intermediary parameter to bridge the gap between image-based detection and actual vehicle size measurement. By detecting the minimum ground clearance point and using it to calculate real-space dimensions, the system achieves accurate vehicle type identification without requiring complex 3D modeling or multiple cameras.
2Measurement precision
If three-dimensional shape models are used for vehicle type identification, then identification accuracy can be improved, but the device complexity increases due to storage and processing requirements
Solution Approach 1:
The patent extracts only the essential dimensional information (length, width, height) from complex three-dimensional shape models, discarding unnecessary surface details and geometric complexity. By focusing solely on dimensional parameters derived from feature point detection and ground clearance measurements, the system achieves accurate vehicle type identification while significantly reducing storage and processing requirements compared to using complete 3D models.
Data Source
AI summary
There is provided a vehicle type identification device including a detection section detecting, based on a vehicle region extracted from a captured image, on an imaging plane, a ground point, a first endpoint, a minimum ground clearance point, a second endpoint, and an upper endpoint of a vehicle, a vehicle width estimation section estimating a vehicle width in a real space based on the ground point, the first endpoint, and the minimum ground clearance point, a vehicle length estimation section estimating a vehicle length in the real space based on the ground point, the first endpoint, and the second endpoint, a vehicle height estimation section estimating a vehicle height in the real space based on the ground point, the first endpoint, and the upper endpoint, and a vehicle type identification section identifying a type of the vehicle based on the vehicle width, the vehicle length, and the vehicle height.