Biometric Boarding Tracking for Passenger Stacking Errors
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Solution Overview
Problem
Biometric boarding systems face inefficiencies due to the 'stacking problem' when passengers stand too close, causing identification errors and delays, and require strict spacing to maintain accuracy, which increases processing time and manual intervention.
Innovation Solution
A method using two-dimensional and three-dimensional image data to track passengers, detect discontinuities in their trajectories, and assign new tracking identifiers when errors occur, allowing for disorderly boarding without significant spacing requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If strict spacing between passengers is maintained to avoid identification errors, then reliability of biometric identification is improved, but boarding time increases significantly
Solution Approach 1:
The system performs preliminary biometric verification by capturing images of multiple passengers simultaneously and pre-processing them before the actual boarding transaction. This allows the system to be ready for immediate identification when passengers reach the boarding point, eliminating the need for sequential processing and reducing overall boarding time while maintaining accuracy.
Solution Approach 2:
The system creates and processes digital copies of passenger biometric data (images and trajectories) rather than requiring physical presence and sequential verification. By working with copied data from captured images, the system can analyze multiple passengers in parallel and perform rapid identification without requiring passengers to maintain strict physical spacing.
2Productivity
If passengers are required to stand close together to minimize boarding time, then productivity is improved, but identification errors increase due to the stacking problem
Solution Approach 1:
The system transitions from two-dimensional image analysis to three-dimensional trajectory analysis by incorporating time as an additional dimension. By tracking the temporal movement and spatial position of passengers through continuous trajectory data, the system can distinguish between passengers who are close in space but separated in time, resolving identification ambiguities without requiring physical spacing.
Solution Approach 2:
The system maintains continuous tracking of passenger trajectories throughout the boarding process, creating an unbroken chain of positional and temporal data. This continuous monitoring allows the system to consistently distinguish between different passengers even when they are in close proximity, maintaining high identification accuracy throughout the entire boarding sequence without interruptions or errors.
3Reliability
If manual intervention is increased to maintain queue spacing and prevent stacking errors, then identification reliability is improved, but automation level decreases
Solution Approach 1:
The system enables self-service automated identification by using algorithmic analysis of trajectory and image data to automatically distinguish between passengers. The computer vision system independently processes spatial and temporal data to resolve stacking problems without human intervention, maintaining high identification accuracy while maximizing automation. The system serves itself by using its own captured data to make identification decisions.
Solution Approach 2:
The system implements closed-loop feedback by continuously monitoring trajectory data and using it to adjust and refine passenger identification decisions in real-time. The feedback mechanism allows the automated system to detect and correct potential identification errors dynamically, maintaining high reliability without requiring manual oversight. The system learns from and responds to the actual boarding process conditions automatically.
Data Source
AI summary
Disclosed is a method for controlling access for at least one tracked object, including:acquiring or receiving a series of two-dimensional images assumed to be taken of the at least one tracked object, and also position data in respect of the at least one tracked object;assigning a unique tracking identifier to the at least one tracked object;determining a trajectory of the at least one tracked object from the position data;determining if there is a discontinuity in the trajectory or data computed from the trajectory, and if a discontinuity is detected, acquiring or receiving one or more new images of the at least tracked object, and assigning a new unique tracking identifier to said at least one tracked object; anddetermining whether access should be allowed, on the basis of at least one of the one or more new images if discontinuity is detected, or on the basis of the at least one image from the series of two-dimensional images if discontinuity is not detected.