Object Detection Apparatus Using Collision Time and Region Overlap
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Solution Overview
Problem
Existing vehicle collision avoidance systems using millimeter-wave radar and monocular cameras may mistakenly recognize different objects as the same due to proximity, leading to inaccurate object detection.
Innovation Solution
An object detection apparatus that defines regions based on radar and camera data, calculating collision times and determining object sameness based on region overlap and time difference within a reference value, ensuring accurate identification of objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If objects detected by radar and camera are determined to be the same based solely on spatial proximity (region overlap), then the determination process is simple, but false positives increase when different objects are in close proximity
Solution Approach 1:
The patent introduces a new parameter (collision time) in addition to the existing spatial parameter (region overlap) to determine object sameness. By changing from a single-parameter to multi-parameter determination approach, the system achieves more accurate object identification while reducing false positives, directly resolving the technical contradiction between determination accuracy and process complexity
Solution Approach 2:
The patent uses collision time as an intermediary parameter to bridge radar detection data and camera detection data. This intermediary enables more reliable object matching by providing an additional verification dimension beyond spatial proximity alone, allowing the system to distinguish between truly identical objects and different objects that happen to be in close proximity
2Reliability
If only spatial region overlap is used to determine object sameness, then the determination is computationally efficient, but accuracy decreases due to false positives from nearby different objects
Solution Approach 1:
The patent adds collision time as an additional determination parameter alongside spatial region overlap. This parameter enhancement improves detection reliability by providing a second verification criterion that filters out false positives, while the computational overhead remains manageable through efficient calculation methods
Data Source
AI summary
In an object detection apparatus, a proximity determination unit determines whether or not a first object and a second object are in close proximity to each other, where the first object is an object detected based on detection information acquired from a radar and the second object is an object detected based on a captured image acquired from a monocular camera. A sameness determination unit determines that the first object and the second object are the same object, if it is determined that the first object and the second object are in close proximity to each other and if a difference between a first collision time with the first object and a second collision time with the second object is less than a reference value.