3D Parking Occupancy Detection via Point Cloud Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current technologies for monitoring truck parking occupancy face challenges such as inaccurate counting and classification due to factors like weather, lighting conditions, and vehicle size, leading to inefficiencies and safety hazards, particularly with commercial heavy vehicles.
Innovation Solution
A system that generates three-dimensional images of parking facilities using Structure from Motion techniques, combining data from multiple cameras to improve detection accuracy and robustness, and employs algorithms like Bundler and Patch-based Multi-View Stereo for precise occupancy classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If 2D camera sensors are used to monitor parking spaces, then the system is simple and cost-effective, but detection accuracy deteriorates due to weather, lighting conditions, and vehicle size variability
Solution Approach 1:
The patent transitions from 2D image processing to 3D point cloud representation. By capturing spatial coordinates (x, y, z) instead of only 2D pixel data, the system achieves robust occupancy detection that is invariant to lighting conditions, weather, and vehicle appearance variations. The 3D geometric structure provides reliable measurements for determining vehicle presence and parking space occupancy.
2Ease of manufacture
If indirect counting technologies are used at ingress-egress points, then the system is easy to implement, but measurement precision deteriorates due to accumulated counting errors
Solution Approach 1:
The patent creates a digital 3D copy of the parking facility and vehicles using point cloud data. This virtual replica allows for direct visualization and analysis of vehicle occupancy without relying on indirect counting methods. The system captures the actual physical state of parking spaces and compares it directly against the digital model, eliminating accumulated counting errors inherent in indirect monitoring approaches.
3Speed
If 2D image processing techniques are used, then processing speed is fast, but detection reliability deteriorates due to occlusions and lighting variations
Solution Approach 1:
The patent employs 3D point cloud data which provides depth information and spatial relationships that are absent in 2D images. This additional dimensional information allows the system to reliably distinguish between occluded objects and actual vehicle presence, and to differentiate vehicles from background elements regardless of lighting conditions. The 3D geometric features remain consistent and reliable for detection purposes.
Data Source
AI summary
Systems and methods for determining park stall occupancy are disclosed herein. The systems and methods include receiving a three dimensional representation of a parking stall in a parking lot. The systems and methods also include processing the three dimensional representation to determine occupancy of the parking stall. The parking stall has a boundary relative to the area.