Object Detection Apparatus Radar Camera Integration
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Solution Overview
Problem
Conventional object detection systems face challenges in accurately combining the sensing functions of radar and camera apparatuses, leading to difficulties in improving detection accuracy, particularly in identifying multiple objects and determining their positions effectively.
Innovation Solution
An object detection apparatus that processes information from both radar and camera systems by calculating reflection intensities, identifying capture regions, extracting edges, converting these regions into markers, determining component regions, grouping them, and identifying objects, thereby enhancing detection accuracy by integrating data from both sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar and camera apparatuses are used individually for object detection, then the detection system is simple, but the object detection accuracy is insufficient
Solution Approach 1:
The patent combines radar and camera apparatuses into an integrated object detection system. The radar apparatus provides distance and speed information while the camera apparatus provides visual identification and classification. By merging the detection results from both apparatuses and processing them together through the object detection unit, the system achieves higher detection accuracy than either apparatus could provide individually, while managing the complexity through unified processing architecture.
2Measurement precision
If the camera apparatus is used to identify the number of target objects and azimuth range, then object detection performance can be improved, but the camera apparatus must deliver high detection performance which increases system requirements
Solution Approach 1:
The patent introduces an object detection unit that acts as an intermediary to process and integrate detection results from both radar and camera apparatuses. This unit combines the distance/speed data from radar with the visual data from the camera, reducing the burden on the camera apparatus to independently identify all object characteristics. The intermediary processing enables effective combination of both sensing functions without requiring the camera to achieve extremely high standalone performance.
3Quantity of substance
If the radar apparatus acquires multiple detection results from one vehicle, then more data is available for analysis, but it becomes difficult to identify the position of the vehicle
Solution Approach 1:
The patent employs feedback mechanisms in the object detection unit that process multiple radar detection results by comparing and correlating them with camera imagery. The system uses the visual information from the camera to provide feedback that helps disambiguate multiple radar detections, determining which radar returns correspond to the same physical vehicle. This feedback loop enables accurate position identification even when the radar apparatus acquires multiple detection results from a single vehicle.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution effectively combines radar and camera data to improve object detection accuracy, enabling precise identification of objects and preventing collisions or intrusions, enhancing both vehicle safety and facility security.
Implementation Method 1
a radar apparatus that transmits a radar signal and receives the reflected signal
Implementation Method 2
the radar signal reflected by an object and being received by the radar apparatus
Data Source
AI summary
A capture region calculation unit calculates a capture point having the local highest reflection intensity in power profile information and calculates a capture region surrounding the capture point. An edge calculation unit calculates the edges of one or more objects from image data. A marker calculation unit calculates a marker from the capture region. A component region calculation unit calculates component regions by extending the marker using the edges. A grouping unit groups component regions belonging to the same object, of the component regions. The object identification unit identifies the types of one or more objects (e.g., large vehicle, small vehicle, bicycle, pedestrian, flight object, bird) on the basis of a target object region resulting from the grouping.