Motorcycle Camera Object Detection Across Changing Roll Angles
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Solution Overview
Problem
The rapid change in roll angle of motorcycles during driving can lead to misdetection of objects, necessitating a robust object detection system that functions irrespective of the motorcycle's roll angle.
Innovation Solution
A method and system for motorcycle camera roll angle robust object detection using concept data structures generated through unsupervised machine learning, which includes generating and matching signatures across different roll angles, enabling object detection without determining the roll angle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional object detection methods are used without considering roll angle, then the detection process is simple and fast, but object detection accuracy deteriorates when the motorcycle roll angle changes dramatically
Solution Approach 1:
The system pre-generates multiple groups of concept data structures representing images at different roll angles before actual detection. When detection is needed, the system already has pre-computed reference data for various roll angles, allowing it to quickly compare and identify objects without performing complex real-time roll angle compensation calculations.
Solution Approach 2:
The detection system dynamically adapts to different roll angles by selecting the appropriate group of concept data structures that matches the current roll angle condition. Instead of using a fixed detection model, the system adjusts its reference data based on the dynamic roll angle state, enabling accurate detection across varying motorcycle orientations.
2Reliability
If multiple groups of concept data structures for different roll angles are generated and stored, then object detection robustness improves, but memory requirements and data processing complexity increase
Solution Approach 1:
The concept data structures are segmented into multiple groups, with each group corresponding to a specific roll angle range. This segmentation allows the system to store and process smaller, more manageable data subsets rather than one large comprehensive dataset, improving both storage efficiency and processing speed.
Solution Approach 2:
Each group of concept data structures serves multiple purposes: it acts as reference data for object detection, provides adaptation to specific roll angle conditions, and enables the system to handle various motorcycle orientations with a single unified framework. This multi-functionality reduces the need for separate specialized data structures for each scenario.
Data Source
AI summary
A method for motorcycle roll angle robust object detection, the method includes receiving, by a processing circuit, an image of an environment of the vehicle, wherein the image was obtained by a camera associated with a motorcycle; and generating, by the processing circuit, a signature of the image; finding, by the processing circuit, using the generated signature, a matching concept data structure out of multiple concept data structures; wherein the multiple concept data structure represents images acquired at multiple roll angles of a field of view of the camera; and detecting, by the processing circuit, within the image, an object or a scenario that is associated with the matching concept data structure.