3D Depth Camera Void Region Detection for Trailer Capacity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Three-dimensional (3D) cameras used in commercial trailer loading have limited ranges, leading to inaccurate data collection and unreliable detection of package walls beyond their range, which affects the accuracy of vehicle storage area capacity diagnostics.
Innovation Solution
A 3D-depth camera system that includes a depth-detection application to identify void data regions and floor data regions within the 3D image data, generating an out-of-range indicator when a package wall is not detected, allowing for accurate modification of graphical representations of vehicle storage area capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a 3D camera is positioned in a large storage area to detect package walls, then the camera can capture depth information, but the camera cannot reliably detect objects beyond its limited range
Solution Approach 1:
The storage area is divided into multiple detection zones based on distance from the camera. The system segments the detection space into near-field (within camera range) and far-field (beyond camera range) regions, allowing different detection strategies to be applied to each segment. This resolves the contradiction by acknowledging that a single camera cannot uniformly detect the entire length of the storage area.
Solution Approach 2:
The system introduces an intermediary processing layer that analyzes 3D image data to identify void regions and infer the presence of package walls beyond camera range. This intermediary analysis mechanism bridges the gap between limited camera range and the need to monitor the entire storage area, enabling detection of objects that the camera cannot directly observe.
2Area of stationary object
If the 3D camera attempts to detect the entire storage area, then complete coverage is achieved, but inaccurate data is produced for objects beyond detection range
Solution Approach 1:
The system dynamically adjusts detection parameters and generates different types of output data based on the detected scene. When package walls are detected within range, detailed depth measurements are provided. When void regions are detected indicating objects beyond range, the system generates indicative data rather than precise measurements. This dynamic adaptation maintains data reliability across the entire coverage area.
Solution Approach 2:
The system uses feedback from the 3D image analysis to determine detection confidence levels. By analyzing the presence of void regions and the completeness of detected surfaces, the system adjusts its output to reflect the actual detection reliability. This feedback mechanism ensures that the reported data accuracy matches the actual detection capability in each region.
3Ease of operation
If moving objects such as people and packages are present in the storage area, then the storage area remains functional, but the 3D camera produces inaccurate data regarding storage area dimensions
Solution Approach 1:
The system performs preliminary analysis of the 3D image data to identify moving objects and distinguish them from stationary package walls before generating final measurements. By pre-identifying void regions and analyzing the context of detected objects, the system can exclude moving objects from dimension calculations, maintaining measurement precision while allowing continuous storage area operation.
Data Source
AI summary
Three-dimensional (3D) depth imaging systems and methods are disclosed for use in commercial trailer loading. In various aspects, a 3D-depth camera is configured and oriented in a direction to capture 3D image data of a vehicle storage area. A depth-detection application (app) executing on one more processors determines, based on the 3D image data, a void data region, and a floor data region within the 3D image data. Based on the determination of the void data region and the floor data region, the depth-detection app generates an out-of-range indicator that indicates that a wall (e.g., a package wall) situated at a rear section of the vehicle storage area is not detected. The determination that a package wall is not detected causes a dashboard app to modify a graphical representation of the capacity of the vehicle storage area.