3D Vehicle Reconstruction from Single Camera Rectangles
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Solution Overview
Problem
Current approaches for three-dimensional reconstruction of vehicles in autonomous driving and driver assistance systems require extensive annotation and are computationally intensive, often relying on multiple sensors or stereo methods, which are costly and inefficient.
Innovation Solution
A method for three-dimensional graphic or pictorial reconstruction using a single camera, where rectangles are captured and analyzed to determine vehicle orientation and structure, allowing for minimal annotation and computation, with the system comprising a camera and computing unit for performing the reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors or stereo methods are used for three-dimensional reconstruction, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent segments the vehicle detection task into multiple detection stages: initial vehicle detection, side detection, and refined 3D parameter extraction. By dividing the complex reconstruction task into manageable segments, the system achieves accurate 3D reconstruction using a single camera rather than requiring multiple sensors working simultaneously.
Solution Approach 2:
The patent transitions from 2D image detection to 3D spatial reconstruction by detecting side orientations and using geometric relationships. The system infers depth and three-dimensional structure by analyzing the orientation of detected sides relative to the camera view, effectively adding dimensional information through computational geometry rather than additional physical sensors.
2Manufacturing precision
If detailed annotation of precise 3D structure is performed, then manufacturing precision is improved, but productivity decreases
Solution Approach 1:
The patent applies partial annotation by detecting only the essential sides of vehicles (front, rear, left, right) rather than annotating every detailed 3D structure element. This partial detection approach provides sufficient information for 3D reconstruction while dramatically reducing annotation time and effort compared to comprehensive detailed annotation.
Solution Approach 2:
The system performs self-service by automatically inferring complete 3D vehicle structures from minimal side detections. Rather than requiring manual annotation of all 3D parameters, the system uses geometric relationships and camera calibration to automatically compute depth, orientation, and dimensional information from the detected sides.
3Ease of operation
If ground plane assumption is used for simple bounding box detection, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent moves beyond the symmetric ground plane assumption by explicitly detecting asymmetric side orientations of vehicles. Instead of assuming all vehicles lie on a flat ground plane, the system detects the actual orientation of vehicle sides relative to the camera, allowing for accurate reconstruction even when vehicles are on inclined surfaces or at various angles.
Data Source
AI summary
A method for the three-dimensional graphic or pictorial reconstruction of a vehicle begins with capturing an image of at least one vehicle with a camera. A first rectangular border of the entire vehicle is captured in the image, to obtain a first rectangle. A second rectangular border of one side of a vehicle is captured in the image, to obtain a second rectangle, and it is determined whether the first and second rectangles are borders which relate to the same vehicle. If so, then it is determined whether a side orientation of the vehicle can be assigned from the two rectangles and, if so, the side orientation is determined. Finally, a three-dimensional reconstruction of the vehicle is performed from the first rectangle, the second rectangle and the side orientation.