Vehicle Exterior Bicycle Recognition Using 3D Region Segmentation
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Solution Overview
Problem
Existing vehicle exterior environment recognition systems face challenges in accurately and promptly identifying bicycles, which can lead to delayed collision avoidance controls and potential collisions due to erroneous detection of three-dimensional objects resembling wheels.
Innovation Solution
A vehicle exterior environment recognition apparatus that includes a three-dimensional object region identification unit, a bicycle determination unit, and a bicycle identification unit, which divides the object region into divisions to determine bicycle-likeliness based on occupation state and identifies the object as a bicycle by considering the presence of a front wheel and rider, enhancing both responsiveness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system detects three-dimensional objects using conventional methods, then it can identify vehicles and perform collision avoidance control, but it erroneously detects objects resembling wheels as bicycles, reducing detection accuracy
Solution Approach 1:
The detection region is divided into multiple divisions (first through fourth divisions) arranged vertically. The system evaluates occupation states in each division separately, checking for specific object characteristics in each zone. This segmentation allows the system to distinguish bicycles from wheel-like objects by analyzing the spatial distribution pattern across divisions, improving detection accuracy without requiring overly complex single-zone detection methods.
2Reliability
If the system waits for complete outline confirmation before identifying bicycles, then detection accuracy improves, but the distance to the bicycle becomes short during postponement, necessitating abrupt collision avoidance actions
Solution Approach 1:
The system performs preliminary identification of bicycles based on partial outline information and occupation state patterns in the divided regions. By establishing identification criteria that can be satisfied with incomplete information (such as specific occupation patterns in certain divisions), the system can identify bicycles earlier in the detection process, reducing the time delay and allowing for smoother, more timely collision avoidance actions rather than waiting for complete outline confirmation.
3Productivity
If the system uses simple object detection methods, then processing speed improves, but it cannot distinguish bicycles from other three-dimensional objects, reducing detection precision
Solution Approach 1:
The detection region is segmented into multiple vertical divisions, and the system evaluates occupation states in each division. This segmentation enables the system to use simple, fast comparison operations against predefined occupation patterns for each division, maintaining high processing speed while achieving accurate bicycle identification through the combined pattern recognition across multiple divisions.
Solution Approach 2:
Different divisions have different evaluation criteria and occupation state requirements. The system applies local quality assessment by checking specific characteristics in specific regions (e.g., wheel-like structures in lower divisions, rider characteristics in upper divisions), allowing efficient local decision-making that contributes to overall accurate bicycle detection without requiring complex global analysis.
Data Source
AI summary
A vehicle exterior environment recognition apparatus includes a three-dimensional object region identification unit, a bicycle determination unit, and a bicycle identification unit. The three-dimensional object region identification unit identifies a three-dimensional object region including a three-dimensional object, in an image. The bicycle determination unit divides the three-dimensional object region into a plurality of divisions, to determine bicycle-likeliness of the three-dimensional object on the basis of a state of occupation of each of the plurality of the divisions by the three-dimensional object. The bicycle identification unit identifies the three-dimensional object as a bicycle on the basis of the bicycle-likeliness.