Monocular 3D Object Detection via Anchor Box Matching
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Solution Overview
Problem
Existing technologies face challenges in detecting three-dimensional objects from two-dimensional images captured by monocular cameras, as they struggle to effectively utilize 2D information to predict 3D information, and increasing the number of anchor boxes improves performance but increases network operation time.
Innovation Solution
A device and method that utilize a monocular camera to obtain a 2D image, where a controller extracts 2D and 3D information for objects by generating 2D and 3D anchor boxes, learning their differences, and matching them to determine 3D object information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of anchor boxes is increased to improve detection performance, then detection accuracy is improved, but network operation time increases
Solution Approach 1:
The patent extracts only the essential 2D information (center coordinates, width, height) from the 2D image to predict 3D object information, rather than processing all anchor boxes. This extraction approach reduces the amount of data processed while maintaining detection accuracy, thereby reducing network operation time.
Solution Approach 2:
The patent transforms the problem from traditional 3D detection by using 2D anchor boxes as an intermediate representation. Instead of directly processing 3D anchor boxes, the system first detects 2D bounding boxes and then infers 3D information, effectively using dimensionality change to reduce computational complexity while preserving detection performance.
2Productivity
If 2D learning results are used to predict 3D information, then processing speed is improved, but detection accuracy deteriorates
Solution Approach 1:
The patent introduces 2D anchor box information as an intermediary between the 2D image input and 3D object detection output. The 2D anchor boxes serve as a bridge that captures essential spatial information from the 2D image, which is then used to predict 3D parameters, maintaining both speed and accuracy.
Solution Approach 2:
The patent performs preliminary detection of 2D anchor boxes and their attributes (center coordinates, width, height) before using this information to predict 3D object information. This preliminary action prepares the essential data structure needed for accurate 3D prediction while maintaining processing efficiency.
Data Source
AI summary
An apparatus and a method for detecting a three-dimensional object includes a camera configured for obtaining a 2D image, and a controller electrically connected to the camera, and the controller extracts 2D information and 3D information for at least one object from the 2D image, and detects 3D object information by utilizing the 2D information and the 3D information.